The May 2026 Financial Stability Review contains a box that anyone worried about equity valuations should read. Its subject is euro-area investors’ exposure to highly valued markets — US technology and AI above all. Cyclically adjusted price/earnings ratios sit well above their own history, US indices well above European ones. Euro-area investors have quadrupled their holdings of US equities over the past decade while only doubling their total equity book, and the fund sector is the single largest holder of both. By the ECB’s own decomposition, roughly 70% of that rise came from valuation effects rather than fresh purchases, and currency moves contributed little. The box builds toward a now-standard worry: thin cash buffers, pockets of leverage, flows that reverse hardest in the most expensive segments, and second-round effects on household wealth and consumption as fund ownership reaches through insurance and pension wrappers.

I am not going to dispute any of that. The valuation read is sound and the transmission story is the right one. What I want to add is the question the supervisory lens leaves implicit — overvalued in what? — and then to follow one thread in the box’s own data, the currency the exposure is denominated in, a little further than the box does. The first runs through most of the piece. The second is where it lands.

A price is a number with a unit inside it

Most valuation arguments smuggle in a unit and a benchmark, then talk as if the result were absolute. CAPE, the measure in the box’s first chart, already does part of the cleaning: it averages real earnings over a decade, stripping inflation out of the denominator, so the FSR is not making the naive nominal-earnings mistake. But the numerator is still a price, and a price is denominated in something. For a euro-area investor that something is the euro. Change the unit, and the level moves.

Here is the S&P 500 — the index those dollar holdings largely track — since January 2015, rebased to 100 and shown in four units. In dollars it is up almost fourfold. In euros, almost exactly the same: across the full decade the exchange rate did little of the work, which is the FSR’s own point. In inflation-adjusted euros it is up about 2.8 times. In gold it is up barely a tenth. The four lines are one price series; none is the index “really” doing what the others are not. No price series comes with a privileged measuring rod attached. A valuation is conditional on a unit — and, the practitioner will add, on a benchmark, a liability structure, and a horizon. Hold the liability structure; it returns at the end.

Note the small gap between the dollar and euro lines. Over ten years it nets to almost nothing, but it is not nothing within the decade: the euro investor ran ahead of the dollar number while the dollar was strong into 2022, then gave it back as the euro firmed. That gap is the exchange rate.

The unit does more than colour the read. How expensive the market looks — in the unit investors and risk managers actually use — can feed position sizing, leverage appetite, and crowding: a market that reads as merely full rather than extreme invites a larger book. On that view the numéraire-dependent read of “expensive” helps shape how much nominal claim gets built in the first place — the stock of leverage and fund assets the acute trigger later acts on. The box’s finding that flows reverse hardest in the most expensive segments is at least consistent with this kind of valuation-sensitive crowding, even if it is evidence about the unwind rather than direct proof of how the position was sized.

The risk premium, measured two ways

The textbook version of the units problem is older than the debate. Modigliani and Cohn argued in 1979 that investors discount real cash flows at nominal rates and misprice the difference; its everyday descendant is comparing an equity earnings yield to a nominal bond yield — subtracting a nominal number from a real one and calling the gap a premium.

Compute the euro-area equity risk premium against the nominal ten-year and against the real ten-year, and the difference between the two readings is, by construction, expected inflation: about 2.8 points at the end of 2022, a little above two now. It is the same lesson as the first chart in a different metric — “stocks look expensive relative to bonds” turns on which yield you put on the other side.

Is some unit better?

If the unit is a choice, the natural reach is for a stable one, and it usually ends at gold. The data ends the reach quickly.

In constant dollars, gold’s January 1980 peak was not durably regained for forty-five years: the nominal price cleared the old high in 2006, but in real terms not until early 2025. A rod that loses much of its real value and needs a generation and a half to recover is no steadier than the currencies it is meant to discipline. The distinction is between a valid unit and a stable one — gold is a perfectly good thing to quote a price in, and its own instability is exactly why switching to it moves the reading. “Cheap in gold” is not firmer measurement, only measurement against a rod that happens to be long right now.

What actually binds

So far this is a piece about measurement, and measurement is a problem for the valuation debate. Whether it is a problem for stability needs the build-up and the trigger held apart.

The build-up metrics are unit-sensitive, in both senses above: the read is conditional on a rod, and the read helps size the position. The acute trigger usually is not. A fund meets redemptions in euros; a margin call is denominated in euros; leverage is a nominal liability the borrower cannot reprice when repricing would help. The dash-for-cash of March 2020 and the 2022 gilt/LDI episode were nominal liquidity spirals, and neither turned on the correct numéraire. So the unit critique bites hardest where nothing acutely binds — what a portfolio is worth, whether an index is dear, how rich a household feels — and barely touches the nominal plumbing that does the forcing.

The clearest place the measuring rod can become part of the margin call is the cross-currency balance sheet, and it is the one the box’s own holdings data draws. A euro fund holding the dollar index has euro liabilities and dollar assets. Redemptions and margin fall due in euros; the assets sold to meet them are priced in dollars. In the calm build-up this is, exactly as the box found, a currency footnote — FX did little. In stress, whether the currency leg helps or hurts depends on the kind of stress. In a classic flight-to-quality the dollar is the haven: it rises as risk assets fall, and for the euro holder the stronger dollar cushions the euro value of the loss. The mismatch bites in the other regime — a dollar-confidence shock, where US assets and the dollar fall together. There the euro fund is hit twice, the asset drawdown and a falling dollar widening the euro loss at the same moment redemptions and margin come due in euros. The numéraire, a footnote in the build-up, becomes the exposure in precisely the stress that is about the unit itself. That state-contingent flip is what the title names.

How far this binds is conditional, and the conditions are what separate it from a generic point about currency mismatch. It binds to the extent the currency exposure is left open rather than hedged; to the extent margin and redemptions fall in the home currency while the assets do not; and to the extent collateral or liquidity transformation leaves the fund short the currency of its liabilities when it most needs it. A fully hedged book with home-currency collateral does not have this problem. An imperfectly hedged one, meeting euro redemptions out of dollar assets under a hedge that itself calls variation margin in stress, does. The seam is specific enough to locate in a given fund’s book.

The map is analytical judgement, not measurement, and is drawn that way. Two questions: does the unit critique change the reading, and does the channel bind acutely? The acute, unit-invariant triggers sit bottom-right — domestic leverage and margin, open-ended fund redemptions. The unit-sensitive items that mostly do not acutely bind sit top-left — equity “overvaluation” as a level, household real wealth — though the level is not a pure non-binder, since, as above, the unit-dependent read may scale the exposure that later does. Cross-currency balance-sheet mismatch sits top-right, the one place both hold at once. Pension and insurance solvency sits between: real or inflation-linked liabilities make nominal-versus-real change the economic-solvency read, and while the channel is slower and better buffered than an FX margin call, a joint inflation-and-FX stress — the scenario where the unit matters most — can move it rightward toward binding faster than the baseline suggests.

The gap, named without a remedy

There is a blind spot here worth naming without pretending to close it. EU fund liquidity stress testing, under the ESMA guidelines in force since 2020, requires managers to stress both assets and liabilities — redemptions above all — and is deliberately principles-based: the manager selects the risk factors the fund’s profile warrants. Asset-side liquidity is the natural focus — how fast holdings can be sold, and at what haircut. The currency-translation leg sits at the seam between market-risk and liquidity-risk testing: a euro fund’s dollar assets, sold into euro redemptions with the exchange rate moving inside the same stress, is a cross-risk interaction that can be under-weighted in practice, especially where the FX hedges themselves call collateral at the wrong moment. Whether a given manager models it is left to the firm. “FX did little in the build-up” — the box’s finding — and “FX does little in stress” are different claims, and the distance between them is the blind spot.

The box ends on household second-round effects — wealth, consumption, the real economy — and that is the right place to end, because it is unit-dependent in just the way this argument has been. A wealth effect is a change in what a portfolio is worth, and worth is denominated in something; the consumption response runs on real purchasing power, a numéraire-sensitive quantity and a slow one. That is why the household channel sits where it does on the map — the rod matters, and it binds gradually if at all. The thing that forces the selling, when selling is forced, is in euros. The clearest place the rod can become part of the margin call is the cross-currency balance sheet the box’s own data describes, under conditions specific enough to look for. Whether it matters in the next cycle I don’t know. It is the part of the map I would watch.

Paweł Fiedor — The Macro Prudential View

The views expressed are the author’s own and do not necessarily reflect those of the Central Bank of Ireland, the European Systemic Risk Board, the Eurosystem, or any other institution with which the author is or has been affiliated.

Sources: European Central Bank, Financial Stability Review, May 2026, box “Drivers of investor behaviour in highly valued equity markets” (Baudino, Bosio, Dieckelmann, Kaufmann and Puga) — https://www.ecb.europa.eu/press/financial-stability-publications/fsr/focus/2026/html/ecb.fsrbox202605_04~fd7b91dd22.en.html; S&P 500, EUR/USD and COMEX gold front-month, Yahoo Finance (^GSPC, EURUSD=X, GC=F); euro-area HICP, Eurostat (prc_hicp_midx) — https://ec.europa.eu/eurostat; forward earnings yield from the NTM price/earnings ratio of the iShares MSCI EMU ETF (EZU), Koyfin / S&P Capital IQ consensus; German ten-year nominal yield, FRED / OECD (IRLTLT01DEM156N) — https://fred.stlouisfed.org; German ten-year expected real rate, Deutsche Bundesbank (BBSEI.M.ERZ.GVB.DE._Z.R10XX) — https://www.bundesbank.de; long-run monthly gold price, DataHub.io — https://datahub.io; US consumer prices, FRED (CPIAUCSL); ESMA, Guidelines on liquidity stress testing in UCITS and AIFs (ESMA34-39-882), in force 30 September 2020 — https://www.esma.europa.eu/document/guidelines-liquidity-stress-testing-in-ucits-and-aifs; F. Modigliani and R. Cohn, “Inflation, Rational Valuation and the Market,” Financial Analysts Journal (1979); J. Y. Campbell and T. Vuolteenaho, “Inflation Illusion and Stock Prices,” American Economic Review (2004). Chart data as cited in each figure.

Macroprudential policy has a working theory of what makes a financial system safe. Keep household leverage from outrunning income. Keep the external position from depending on financing that can reverse overnight. Hold down currency mismatches on unhedged balance sheets. Lean against the procyclical build-up of all three. The toolkit — countercyclical capital buffers, loan-to-value and debt-service limits, restrictions on foreign-currency lending — is a set of instruments for producing a balance sheet that can take a shock without amplifying it.

Poland arrived at the 2008–09 crisis with much of that balance sheet already in place, and largely before it had the tools. The modern Polish framework — the systemic risk board, the activated buffers, the borrower-based measures — came mostly after 2011, after the events that made Poland look resilient. The resilience came first. My argument is that it came in significant part from the composition of Polish growth: not the headline rate of expansion but what the expansion ran on and how it was financed. By the time the crisis arrived, Poland already had several of the balance-sheet characteristics that macroprudential policy later seeks to preserve.

It did not have all of them. The same growth that kept aggregate leverage moderate sat on top of a Swiss-franc mortgage stock larger, in absolute terms, than Hungary’s. That is not a footnote to the argument; it is the argument’s other half. Poland’s growth composition was strong on two counts and weak on a third, and the count it failed on produced a concentrated vulnerability that the favourable aggregate picture could not see and that fifteen years of resolution has still not cleared. Aggregate resilience and concentrated fragility on the same balance sheet — that recurring pattern is the through-line of this piece. It appears before the crisis in the foreign-currency mortgage book, and it appears today in a deeply negative credit gap sitting over a flagged housing-market risk. The aggregate flatters; the concentration bites; the distance between them is where the macroprudential questions live.

A word on what this is. It is a structured comparison across a handful of European economies through one shock, not an identification strategy. The things I am separating — leverage, external financing, currency mismatch, real-economy structure, the exchange-rate regime — co-moved in the countries that had them, and I make no claim to have isolated any one. To keep the central term from swallowing everything, I use growth composition narrowly, in three parts: the leverage intensity of the expansion, the currency in which that leverage is denominated, and the liability structure of the external financing behind it. Two things sit deliberately outside that definition. A country’s structural endowment — domestic-market size, trade openness, sectoral concentration — is largely inherited rather than chosen, and it turns out to matter as much. The exchange-rate regime is a monetary choice that transmits the balance sheet into outcomes rather than forming part of it. Keeping these three layers apart is what stops “composition” from becoming a synonym for “everything that went right,” and it is what lets the argument concede, later, that composition was not always the decisive layer.

One thing this definition leaves out is worth naming rather than smuggling past. The sectoral destination of credit — whether the borrowing built tradable-sector capacity or financed property and consumption — is a genuine determinant of long-run resilience, and two economies identical on my three counts could differ sharply on it. I scope it out here on purpose: the evidence in this piece is about the financial structure of the expansion and the balance sheet it left behind, not about where the credit was ultimately deployed, and that allocation question deserves its own treatment rather than a fourth column bolted onto this one.

The puzzle

Poland was the only EU economy to avoid a recession in 2009. The point worth pressing is comparative, because Poland was not the only fast-growing economy in the region beforehand. Latvia, Hungary and the rest of the CEE bloc were converging on Western European incomes at speed; Spain was doing the same inside the euro area. They were all growing. The chart shows the growth resolving into a spectrum of outcomes rather than a clean binary, from Poland’s continued expansion through Czechia’s and Hungary’s moderate dips to Latvia’s collapse.

Headline GDP conceals the difference because it counts output regardless of what produced it. An economy expanding on a property and consumption boom financed by reversible foreign capital and one expanding on productivity and employment post similar numbers and carry different risks. The macroprudential question is whether the difference is legible before the shock rather than only in the wreckage.

One country should make the argument nervous from the start, so I will name it now. Czechia had a floating currency and low household leverage — much of what I am about to credit Poland with — and still contracted close to 5% in 2009. Hold that case. It is the test the argument has to pass, and I return to it once the mechanism is visible, because Czechia does not break the thesis so much as fix its limits.

Aggregate leverage

By 2010 Polish household credit stood near 36% of GDP, Czechia’s at 30%, Hungary’s at 25%. Spain’s was 73% and had peaked near 86%. These are not points on the same distribution. Spain and the euro-area periphery had undergone a financial deepening of a different order, much of it into residential property; the CEE economies were building leverage from a lower base and more slowly. Polish credit grew, but in proportion to an economy itself expanding fast — leverage added to a denominator that was genuinely enlarging.

This is a leverage measure, not a decomposition of growth into productive and unproductive parts, and it should not be asked to carry more than it can. It does not establish that Polish growth was productivity-led and Spanish growth was not. It establishes something narrower: entering the crisis, Polish and Czech household balance sheets carried far less debt relative to income than Spanish ones, and were correspondingly less exposed to debt-deflation and to a rise in debt-service costs. That is the balance-sheet outcome a borrower-based macroprudential regime exists to produce, and Poland had it without yet having the regime. On the first of composition’s three counts — leverage intensity — Poland scored well.

The Hungarian line does something the others do not. It jumps, from around 37% in 2009 to 41% by mid-2010, then slides. That movement is not new lending; it is the forint depreciating and revaluing a stock of foreign-currency mortgages upward in domestic-currency terms. Ordinary credit does not behave like that. The line is carrying a currency mismatch, which is the cue to look at the mismatch directly — because Poland was carrying a larger one, and that is the count on which it did not score well.

The mismatch underneath

Poland’s household FX loans — overwhelmingly Swiss-franc mortgages — peaked near €50bn in July 2011, larger in absolute terms than Hungary’s €21bn, the exposure usually cited as the cautionary CEE case. This is the second count of composition, currency denomination, and Poland scored badly on it. The point needs stating carefully, because it is easy to overstate in either direction. The mismatch did not mean Poland’s aggregate leverage was secretly high: the €50bn book was around 13% of GDP, roughly a third of a household-credit ratio that was itself low, and stripping it out would leave Polish leverage lower still, not higher. Cheap Swiss-franc credit expanded mortgage access; it did not disguise a domestic-currency binge that would otherwise show. Low leverage and a concentrated currency mismatch genuinely coexisted. But a leverage ratio that is low and a third unhedged foreign currency is worth less as reassurance than the ratio alone suggests, which is exactly why currency denomination belongs inside the definition of composition and not outside it. Poland’s composition was mixed: strong on volume, weak on denomination.

Where did the denomination failure come from? Partly from the growth model, but not as cleanly as a tidy story would want. A fast-converging economy runs structurally higher inflation and therefore higher policy rates than the core, and the gap between złoty and Swiss-franc rates was wide and persistent; that differential created the pricing incentive for households to borrow in francs. The convergence process that shaped Poland’s macro balance also helped create the incentive for the mismatch. But the incentive was not the scale. Czechia and Romania were converging floaters with rate differentials of their own and did not build Poland-scale franc books; the differential was necessary, not sufficient. What turned an incentive into €50bn was supervisory tolerance of unhedged foreign-currency lending to households and the competition among foreign-owned banks to write it. The growth model lit the incentive; supervision and bank competition let it run. That distinction matters, because it locates the failure precisely where a tool could have acted — a cap or ban on foreign-currency lending to unhedged borrowers — and Poland’s tools were absent or weak through the build-up.

How the two stocks were resolved is a separate question from how they were built, and it runs along a different axis again: not growth composition but the capacity and willingness to act. Hungary extinguished its FX mortgage book almost completely through a forced conversion in 2014–15, converting borrowers to forint by statute, pushing the currency risk onto the banks, the exposure gone in roughly a quarter. Poland did not. Its stock has come down slowly, through amortisation and, since around 2020, through individual litigation, with Polish courts and the Court of Justice of the EU annulling Swiss-franc contracts on consumer-protection grounds. By mid-2022 the ESRB recorded almost 30% of CHF contracts in litigation; about €9bn remained outstanding in early 2026, with provisioning against the litigation a continuing drag on bank profitability.

On the narrow metric macroprudential authorities weigh most heavily — the speed with which a systemic mismatch leaves bank balance sheets — Hungary did better, doing in a quarter what Poland has not finished in fifteen years. Whether it did better overall is genuinely unsettled. Forced conversion carried a cost that does not appear as a balance-sheet line: a state that rewrites financial contracts by statute may raise the premium it later pays for bank and sovereign funding, with second-round effects on credit supply, though how large that cost was, and whether it exceeded the drag of Poland’s fifteen-year litigation overhang, is not something the evidence here settles. What the comparison does show is cleaner than a verdict. Hungary had the worse growth model and the greater resolution capacity, and used it; Poland had the better model and let the mismatch sit. Resolution capacity and growth composition are different things, and a country can be strong in one and weak in the other.

With both halves on the table — composition strong on leverage, weak on denomination, and resolution a separate axis entirely — the rest of the piece concerns the third count, external financing, and why Poland’s aggregate position held when the shock came.

What financed the deficit

Latvia ran current account deficits above 21% of GDP in 2006 and 2007; when the financing stopped in late 2008 the deficit swung to surplus within a year, but only because imports collapsed and output fell by a fifth. Spain, inside the euro and so without the same risk of abrupt currency-driven flight, ran deficits near 9% and adjusted slowly through years of internal grind. Poland’s deficits stayed in the mid-single digits — not dramatically smaller than Hungary’s, and at points not far from Spain’s. The size of the deficit is not what set Poland apart. What differed was the liability side: how the deficit was financed, and how reversible that financing was.

The contrast is the point, and it is one of scale and reversibility rather than of one pure financing type against another. Latvia financed its deficit overwhelmingly through short-term cross-border bank funding, the bulk of it from Swedish parents — Swedbank and SEB — lending into their Baltic subsidiaries and onward into real estate. That funding ran past 37% of GDP at its 2007 peak, and it reverses on a trigger: in 2009 it went sharply negative as the parents pulled back. The Riksbank’s own retrospective identifies the Baltic crisis as a combination of fixed exchange rates, foreign-currency debt and heavy parent-company funding of bank subsidiaries; the ECB describes those banks coming under acute pressure when intragroup liquidity seized. Poland’s bank-funding component never approached that scale — it peaked around 7% of GDP — and it did not reverse in 2009. Poland’s inflows were spread across direct investment, portfolio investment and bank funding rather than concentrated in the one category that runs.

Three honest qualifications keep this from overreaching, and none of them dissolves the contrast. First, the categories are not airtight: portfolio investment is not a stable flow, and over the period it was at times Poland’s largest single inflow, so the claim is not that Poland leaned on sticky FDI but that it leaned far less on the specific reversible funding — short-term parent-bank lines — that turned the Baltic deficit into a sudden stop. Second, a meaningful share of Poland’s FDI went into the banking sector itself, foreign parents capitalising their Polish subsidiaries to fund exactly the retail-lending expansion, including the Swiss-franc mortgages, that produced the mismatch above; the liability structure governs rollover and sudden-stop risk, and on that it protected Poland, but it does nothing about the asset-side currency mismatch the same capital helped fund. Third, Poland’s own mix shifted under stress, with the bank-funding component rising in 2006–08, visible in the chart. The defensible claim is bounded and is enough: Poland’s external financing was structurally less reliant on the funding that can be cut in a quarter, which is why it avoided the sudden stop that crushed Latvia — and that is a different protection from the one the FX book needed and did not get.

What absorbed the shock

The exchange-rate regime is a monetary choice, not a feature of how Poland grew, and the two should not be merged. The złoty’s roughly 30% depreciation between mid-2008 and early 2009 said nothing about Polish growth composition; it reflected a decision to float. What the float did was transmit the balance sheet Poland brought to the crisis into the output it recorded through it. For an economy with a large tradable sector and a household balance sheet not catastrophically short foreign currency, depreciation works as a shock absorber: exports cheapen as domestic demand weakens, and the balance-sheet damage from the weaker currency stays contained.

That second condition is why the easy version — floaters absorb, pegs cannot — needs qualifying, and the qualification runs straight back through the FX chart. Depreciation absorbs a shock only where private balance sheets are not fatally short foreign currency. Hungary floated, and for Hungarian households with forint incomes and Swiss-franc mortgages the depreciation deepened the damage rather than cushioning it; the same currency move that helped Polish exporters tightened the screw on Hungarian and many Polish FX borrowers. The pegged Baltics sat at the other pole, unable to depreciate at all, and took the entire external adjustment through internal devaluation — falling wages, prices and employment, the channel that manufactures non-performing loans and the reason Latvian output fell by a fifth. The float did not create Poland’s resilience. It transmitted a balance sheet that was resilient at the aggregate level, and only to the extent that it was.

Czechia, and the part composition leaves out

Now the case held back. Czechia had a float and low household leverage — good marks on composition as I have defined it — and still contracted close to 5% in 2009. On composition alone the thesis would not survive it.

It survives because resilience required more than good composition, and Czechia is where the structural endowment I set aside earlier does its work. Czechia’s recession came through trade: a small, extremely open economy wired into German manufacturing supply chains, hit hard when those chains contracted in late 2008. A floating koruna helped at the margin but could not offset a collapse in foreign demand for the goods Czechia made. Poland’s larger domestic market and lower trade openness gave the złoty’s depreciation more to work with — more domestic demand to defend and proportionally less exposure to the single channel that carried the shock into Czechia.

I separated endowment from composition at the outset precisely so this would not read as the thesis stretching to absorb its counterexample. Domestic-market size and trade structure are not features of how a country chose to grow; they are largely inherited, and in Czechia’s case the inheritance was decisive. But the right conclusion is not that endowment beats composition and the article should pack up. It is that composition and endowment are distinct failure modes, and in this episode they produced damage of different depth. The countries undone by composition took the deep hits: Latvia, financed by funding that vanished, lost more than a fifth of output; Spain, carrying household leverage near 86% of GDP, lost most of a decade. The country undone by endowment took a shallower, recoverable one: Czechia contracted around 5% and was back above its pre-crisis level by 2010. I would not build a general law out of three outcomes from a single crisis. What this configuration shows is narrower and still useful: when the shock hit, the largest collapses sat with the financing and leverage failures, while a trade-endowment shock produced a normal recession Czechia walked out of. Composition was not the only thing that determined whether a shock was survived, but here it was the layer that travelled with the outcomes a supervisor most wants to avoid.

What I am not ruling out

Poland’s resilience is overdetermined, and honesty requires conceding that some of the omitted factors may be first-order rather than additive. EU structural funds were not merely a helpful inflow; they were a non-reversible source of external financing during precisely the window when private capital retreated, and a stabiliser of that kind weakens how far the Polish case generalises to converging economies without an EU anchor. Foreign-bank ownership, common across the region, interacted with Polish supervision and home-host arrangements differently than in the Baltics, in ways that are about supervisory practice as much as funding structure. Pre-crisis house-price excess was milder than in Spain or the Baltics. Fiscal space let the automatic stabilisers run. The absence of US securitisation exposure spared Poland the first-round hit. A large domestic market — which I have filed under endowment — may simply be one of the principal reasons Poland could absorb the external shock at all.

The claim is therefore not that growth composition was the cause, nor that it can be isolated from the bundle it travelled with. It is that composition is a coherent and observable organising lens for part of that bundle, that it sits upstream of the specific vulnerabilities macroprudential authorities track, and that it was legible in the balance sheet before the shock — which is more than can be said for “Poland was lucky,” a description of the outcome rather than the structure that produced it.

Where Poland stands now

The credit-to-GDP gap is the indicator the Basel framework uses to signal whether a countercyclical buffer should be switched on; above +2 percentage points is the conventional activation level. Poland’s gap has been below that for over a decade and now sits around −17pp, having reached −23pp in 2023. Read literally, there is no credit boom in Poland and the economy is accumulating macroprudential space rather than spending it, which is why Poland’s authorities have kept the buffer rate inactive for most of the period.

The literal reading is the one to resist. A deeply negative gap is a descriptive residual — credit has grown more slowly than output — and a residual has several possible causes. Polish credit has been suppressed on the supply side as much as moderated on the demand side: a bank asset tax since 2016 that penalises lending relative to holding government securities, and capital tied up against the CHF litigation described earlier. Nominal output outrunning credit is consistent with a safe, well-balanced economy; it is equally consistent with a banking sector taxed and litigated into caution. The BIS gap is also known to be unstable in real time, sensitive to the trend it is measured against. I read it as a description of where credit sits relative to output, not as a verdict that Poland is safe.

The sectoral picture is where the verdict lives, and it returns to the through-line. The ESRB’s most recent residential real estate assessment still classifies Poland as medium stock risk, citing accelerating house prices, elevated debt-service ratios on new lending, a high share of variable-rate loans and the unresolved Swiss-franc legacy. A deeply negative aggregate gap sitting over a flagged housing vulnerability is the same configuration as the pre-crisis balance sheet: aggregate moderation on top of a concentration the aggregate cannot see. Fifteen years ago the concentration was a foreign-currency mortgage book; today it is the housing market and what remains of that same book. The instruments differ in resolution, and the coarser one flatters.

What this implies

For most of the period that matters here Poland barely had a macroprudential framework in the modern sense; the institutions and tools arrived largely after 2011, after the events that made Poland look resilient. The resilience came first, from the structure of the economy rather than from prudential policy applied to it.

That has an implication for the people who run these frameworks, and it is sharper than “monitor the growth model,” which is not an operational instruction. The lesson is about which tools sit where in the framework. Poland’s Swiss-franc book built up while aggregate credit stayed moderate, which means the credit-to-GDP gap — the cyclical indicator that anchors the countercyclical buffer — would never have flagged it: a concentrated currency mismatch is not a volume boom, and the gap is built to see volume booms. The borrower-based measures that catch this class of risk — caps on debt-service ratios, limits or bans on unhedged foreign-currency lending — are not cyclical switches a supervisor flips when a dashboard turns red. They are structural underwriting standards, and the Polish case is an argument for treating them that way: in place as a permanent baseline rather than held in reserve for a cyclical signal that, by construction, will not arrive in time for a risk that is not also a boom. Composition metrics earn their place a step below that: not as automatic triggers, but as the early evidence that justifies heightened scrutiny and informs how tightly the structural measures are calibrated. The currency denomination of household leverage, the share of external financing in reversible bank funding, the concentration of the real economy on single external channels: all were legible in Poland’s and Latvia’s data well before 2008, and all speak to risks the cyclical anchor cannot register. The contestable claim is not that supervisors should add three indicators to a dashboard; many already track them. It is that the framework should not depend on the cyclical gap to call for the structural tools, because for this class of risk the gap is the wrong instrument and will stay silent while the exposure builds.

The boundary on all of this is the FX book itself. Good composition on two of three counts did not stop Poland accumulating a Swiss-franc stock larger than Hungary’s; the growth model lit the incentive and supervision let it run; and neither composition nor surveillance resolved it, which is why the stock and the housing risk beside it are still on the ESRB’s list. Reading the terrain earlier is worth doing. It is not a substitute for holding the borrower-based instruments that catch what the terrain leaves exposed, nor for the supervisory willingness to use them — the count on which Hungary, with the worse model, outperformed.

Poland’s 2009 outcome was the right one, and the structure that produced it was partly legible in advance. The unresolved Swiss-franc book is the wrong one, on the same charts, fifteen years on. A resilient aggregate is worth having. It is not, on its own, the same thing as a safe one.

Paweł Fiedor — The Macro Prudential View

The views expressed are the author’s own and do not necessarily reflect those of any institution with which the author is or has been affiliated.

Sources: Eurostat, national accounts — GDP and main components, chain-linked volumes (nama_10_gdp) — https://ec.europa.eu/eurostat; Eurostat, balance of payments by country, current account and financial account (bop_c6_a), and GDP at market prices (nama_10_gdp), author calculations; BIS, Total Credit Statistics — credit to households and NPISHs, % of GDP, adjusted for breaks — https://www.bis.org/statistics/totcredit.htm; BIS, credit-to-GDP gaps (private non-financial sector) — https://www.bis.org/statistics/c_gaps.htm; Basel Committee on Banking Supervision, Guidance for national authorities operating the countercyclical capital buffer (December 2010) — https://www.bis.org/publ/bcbs187.htm; ECB, Statistical Data Warehouse — euro reference exchange rates (EXR) and MFI balance sheet items, loans to households in foreign currency (BSI) — https://data.ecb.europa.eu; Z. Zimny, Inward FDI-Related Challenges to Poland's Further Economic Progress (2015) — https://www.davidpublisher.com/Public/uploads/Contribute/56d3febf33bd9.pdf; Sveriges Riksbank, Financial crisis preparedness in the Nordic-Baltic region, Economic Commentary (2025) — https://www.riksbank.se; ECB Banking Supervision, Financial integration in the Baltics: lessons in resilience and transformation (4 October 2024) — https://www.bankingsupervision.europa.eu/press/speeches/date/2024/html/ssm.sp241004~9588c58d39.en.html; Peterson Institute for International Economics, Baltic Protests and Financial Meltdowns — https://www.piie.com/commentary/op-eds/baltic-protests-and-financial-meltdowns; European Systemic Risk Board, Follow-up report on vulnerabilities in the residential real estate sectors of the EEA countries (February 2024) — https://www.esrb.europa.eu/pub/pdf/reports/esrb.report.vulnerabilitiesresidentialrealestatesectors202402~df77b00f9a.en.pdf; European Systemic Risk Board, national macroprudential measures database — https://www.esrb.europa.eu/national_policy/; M. Piątkowski, Europe's Growth Champion: Insights from the Economic Rise of Poland (Oxford University Press, 2018). Chart data as cited in each figure.

The claim

The thing that makes a risk macroprudential is not that it is large. It is that it is correlated — that many institutions fail in the same way at the same time because they share an exposure. A maturity mismatch at one bank is that bank’s problem; the same mismatch across a funding market, snapping shut on the same morning, is a system’s problem. Supervision is organised around finding those shared exposures and stress-testing what happens when they crystallise together.

There is a class of shared exposure the framework does not look at this way, because it files it under operational risk and operational risk under IT. The financial system runs on a thin, concentrated layer of common substrate: a handful of core-banking platforms, a few cloud providers, a small set of security-tooling vendors, one public-key infrastructure underneath authentication almost everywhere. A flaw in any of those is a correlated exposure across every institution standing on it, and that correlation is the systemic content. Two developments in 2026 made the point concrete, and both are currently treated as engineering questions rather than stability ones. That treatment is the categorisation error this piece is about.

One disciplining caveat governs everything that follows, and I would rather state it once, plainly, than dress it up. In both cases the threat is, today, better evidenced on paper than in the world: demonstrated in controlled settings, or estimated on the page, but not executed against hardened financial infrastructure at scale. I mark claims as established, plausible, or speculative throughout, because the distance between those three is the analysis. The two cases are also not symmetric, and I will not pretend otherwise — the first is the live, uncertain one everyone is talking about; the second is slower-moving but far more certain in direction. They are weighted accordingly.

Case 1: offensive capability is outrunning the cadence of supervisory testing

In the first week of April 2026, Anthropic published a model it declined to sell. Claude Mythos Preview was presented not as a product but as a capability judged too sensitive for ordinary release: a system that finds previously unknown software vulnerabilities and writes working exploits for them with limited human direction. Rather than ship it through an API, Anthropic restricted it to a vetted consortium of around fifty organisations under a programme called Project Glasswing, and reported that in its first month it had surfaced more than ten thousand high- or critical-severity flaws. For nearly two months not one European bank, regulator or government could use it; on 1 June, after the European Commission flew officials to San Francisco, Anthropic agreed to admit the EU’s cybersecurity agency, ENISA, to the programme. The manner of that admission — a bilateral concession in response to a direct ask, rather than the exercise of any European instrument — is itself part of the argument here, and I will come back to it.

The precise capability claim matters, because the overclaimed version invites dismissal and the defensible version does not. What is established: the UK’s AI Security Institute, evaluating the model independently, found it the first to complete a thirty-two-step simulated intrusion — reconnaissance through to full network takeover — that AISI estimates at around twenty expert-hours, and found it able to discover and exploit vulnerabilities autonomously in controlled settings. What AISI states with equal clarity, and what bounds the claim: those environments were small, weakly defended, and lacked the active defenders, segmentation and endpoint tooling of a real enterprise network. The defensible statement is therefore narrow. A model has shown benchmark-tier offensive capability against soft targets. It has not been shown to defeat a hardened, actively defended bank at scale. Everything systemic downstream is conditional on that benchmark-to-production gap closing, which is plausible, not established.

Set against this is the one long-run resilience series the field has.

Mandiant’s global median dwell time — the days an intruder sits undetected inside a network after breaking in — has fallen from 416 in 2011 to the low teens. It is worth being exact about what that shows, because it is easy to misread. Dwell time is measured after a breach succeeds; it captures how fast defenders notice an adversary already inside. Autonomous vulnerability discovery acts before the breach, compressing the work of finding and weaponising a flaw, which raises the probability and frequency of initial compromise. Those are different phases of an attack, and a model that writes a zero-day in minutes changes nothing about dwell time once an attacker is in. So the series says nothing about attacker-side compression. What it does show is narrower and still useful: defence has a measurable cadence, won over a decade against human adversaries at human speed. The open question is whether the pre-intrusion phase is about to move on a timescale that cadence was never set against.

There is a specific supervisory exposure here, though it is narrower than earlier versions of this argument implied, and worth scoping precisely. The Digital Operational Resilience Act’s threat-led penetration testing regime, built on TIBER-EU, is intelligence-led and largely tests the post-compromise contest: given a foothold, can the institution’s defenders detect lateral movement, privilege escalation and exfiltration. A faster initial breach vector does not, by itself, degrade that — the red team can simply begin from the assumed breach, and the blue-team detection it certifies stays comparable. So the honest version is not that AI breaks threat-led testing. It is twofold and smaller. First, AISI’s own ranges show these models executing the whole chain autonomously, including the lateral movement and escalation that TLPT exists to test, which raises the question of whether a red team that lacks frontier tooling is exercising the blue team against the speed and breadth the real adversary now brings. Second, and this is the durable point, an EU red team operating below the offensive frontier — because the most capable tooling is access-restricted — tests against a weaker adversary than the one that exists, and certifies detection against that weaker adversary. That is a calibration concern about the realism of the exercise, not a claim that the instrument is broken; it is one supporting strand, not the load-bearing one.

What actually carries the case is the trend, and here the evaluator is explicit. AISI found a second model, from a different developer, reaching the same tier weeks after the first, and concluded the capability is emerging as a byproduct of general improvements in autonomy, reasoning and coding — with further increases expected “in quick succession.” That is the systemic content: not one fenced tool, but a frontier that is moving, broadening across developers, and only contingently access-restricted.

The scope of the claim has to be drawn carefully, because the obvious rebuttal is correct as far as it goes. Most of a European bank’s defensive patching is inherited: global vendors fix a flaw once and push it everywhere, and several of those vendors — Microsoft, Google, AWS, CrowdStrike, Cisco — sit inside the Glasswing consortium. A better red-team tool does not let a bank rewrite a vendor’s source code; it cannot fix what only the vendor can fix. So the margin that matters is not patch distribution, where Europe is largely fine. It is the residual window between a frontier-grade flaw being exploitable and the vendor’s fix arriving — the interval in which detection, containment and response, not patching, are the only defence. That residual window is exactly where first-party capability and testing realism decide the outcome. The claim is not that Europe cannot defend itself. It is that the supervisory exercise certifying it can detect a frontier intrusion may be calibrated, through restricted access to the best offensive tooling, to an adversary slower and narrower than the one that now exists.

The access picture sits behind this, and it should be stated as documented participation rather than absolute exclusion. Per Wall Street Journal and Bloomberg reporting: the consortium is mainly US-based; the NSA had access through earlier arrangements; Anthropic’s proposal to widen the group from around fifty to around a hundred and twenty organisations was blocked by the Trump administration, citing misuse risk and concern that broader access would dilute the federal government’s own use. Euro-area finance ministers met in Brussels on 4 May to discuss the lack of European access; the negotiations that followed ran for weeks without result, until the Commission sent officials to San Francisco and, on 1 June, Anthropic agreed to admit ENISA. That outcome is worth reading carefully rather than as simple closure. Europe obtained access to a capability that can be used against its own infrastructure not through any instrument it holds — the AI Act regulates deployment inside the Union and cannot compel an American firm to grant access to a model that sits outside it — but through a bilateral concession secured by travelling to ask for one. A single agency inside a testing consortium is also not a supervisory regime with standing access. So the asymmetry was real and it was contingent: it lasted under two months, then bent to a flight and a request, which says both that the fence was never structural and that Europe’s leverage ran through diplomacy rather than through the regulatory apparatus meant to govern operational resilience.

That reading was overtaken within weeks: in mid-June the US, citing national-security authorities, issued an export-control directive suspending all foreign-national access to Mythos and Fable (its guardrailed public release), forcing Anthropic to disable both for every customer, ENISA’s new access included — Anthropic disputes the basis and says it is working to restore service. Inside six weeks European access went from withheld, to granted by concession, to suspended by a US national-security order that no European instrument could reach or reverse.

The hinge: transient or structural?

That question — passing condition or standing feature — is where the macroprudential weight of Case 1 turns, and I do not think it is currently answerable. The evidence points both ways.

The case that the frontier keeps tilting starts with compute. Frontier training compute has grown roughly four-to-five-fold a year since 2010; my fit to Epoch AI’s frontier-model series returns 4.6×. Extended to 2030, that reaches about 10²⁹ floating-point operations — close to where Epoch’s own analysis puts the ceiling of what electricity can deliver, power binding ahead of chips and data. So one reading is an established trend running into a plausible physical ceiling: the offensive frontier plateaus, and the asymmetry is transient.

The counter-case is not weak. DeepSeek-V3 reached near-frontier capability at perhaps a tenth of the compute of its contemporaries, for a reported final-training-run cost of around $5.6 million — a figure that excludes prior research and ablations and has been widely misreported as total project cost. If algorithmic efficiency keeps improving — Epoch estimates roughly a halving of the compute needed for fixed capability every nine months — a power ceiling on training need not cap capability, because capability can be bought with cleverness instead of electricity. The qualification cuts back toward transience: efficiency has its own diminishing returns, and a power limit is physical in a way ingenuity is not. Neither side is settled.

And DeepSeek is Chinese, which dissolves the clean “fenced by Washington” story rather than complicating it. If frontier-adjacent offensive capability can be reached for single-digit millions outside the US, the consortium’s control is contingent and probably temporary, which is the reason I will not call the asymmetry structural. The fencing is real now; efficiency diffusion is why it may not last; the implication is multipolar rather than US-favouring. That contradiction is better made the argument than hidden: Case 1 is acute and quite possibly transient, and should be sized as such.

One corroboration keeps the near-term reading alive. AISI evaluated OpenAI’s GPT-5.5 on the same battery and placed it in the same tier — the second model to complete the thirty-two-step intrusion, marginally ahead on some narrow metrics. Two labs reaching the same capability independently is harder to contain than one. The same caveat governs throughout: these are benchmark environments without active defenders, so what is established is benchmark-tier capability while the operational threat stays speculative. The gap between the two is the room in which red-team standards and model-assisted defence have time to adapt, slowly but not at zero.

Case 2: the loss is created at capture, not at decryption

The quantum threat is mostly hype, and for most of its advertised uses the skepticism is earned. The physicist Sabine Hossenfelder has put the sharp version: across finance, logistics, chemistry and materials, quantum computing has consistently failed to convert a theoretical advantage into a practical one, and the lone clear exception is codebreaking. For a financial-stability reader that is the load-bearing simplification — it sets aside the portfolio-optimisation claims that rarely survive their implementation costs and isolates the one capability with a systemic payoff: breaking the public-key cryptography that protects stored data and underpins authentication.

That capability splits into two channels, and collapsing them — or waving the threat away as “just privacy” — misses half of it. Google’s March 2026 post setting its own migration deadline draws the line precisely: the threat to encryption is present today through harvest-now-decrypt-later, while the threat to digital signatures and authentication is a future one that must be fixed before a cryptographically relevant machine exists.

The first channel is confidentiality.

An adversary who captures encrypted traffic or an archive today can store it and read it whenever a capable machine arrives; for data whose confidentiality must outlast that arrival, the loss is booked at capture, not decryption. This is the one place a time-separation genuinely does analytical work that concentration alone does not — the exposure and its crystallisation are split across an interval no one can date. A risk officer will rightly push back, and the answer concedes before it holds: not everything is harvested, storage and targeting cost money, and much traffic already uses forward secrecy and short-lived keys. So the channel is real but selective — the marginal exposure concentrates in high-value, long-horizon, poorly-rotated stores: custody records, certain pension and mortgage books, sovereign archives. That is narrower than “the loss is fully booked,” and it is the defensible claim.

The second channel is integrity and availability, and the obvious version of it is wrong. It is tempting to say a quantum computer could forge clearing instructions and inject fraudulent payments. It could not, at least not that way: core interbank messaging and real-time gross settlement rely heavily on symmetric message authentication, which Shor’s algorithm does not break and which a larger key handles. Mass-forging a TARGET2 instruction is not the threat. The exposure is one layer down, in the asymmetric public-key infrastructure that authenticates endpoints, establishes secure channels, issues the certificates counterparties trust, and signs the software updates institutions install. That PKI is pervasive across financial infrastructure — it is what the sector’s own post-quantum migration guides catalogue first — and it is what a cryptographically relevant machine breaks.

The realistic systemic event is not silent, prolonged impersonation; it is more likely a forced halt. Once a certificate hierarchy is known to be breakable, the rational response is to revoke trust in the compromised roots, at which point connections fail closed: secure channels drop, handshakes are refused, and institutions fall back to out-of-band verification and manual settlement. How far that propagates depends on which trust anchors are shared across how much critical infrastructure — existing revocation procedures, segmented trust and out-of-band fallbacks are precisely the controls that would bound it — so the plausible range runs from messy-but-contained disruption to something much wider, rather than an automatic continent-scale outage. But the direction is a denial of service on the trust layer rather than a quiet looting of the system, which is the more credible worry: a system that has lost confidence in its own certificates stops rather than continues corrupted. The integrity exposure lives in the narrower, nastier windows around that halt — the period before the break is recognised, and the migration itself, in which a maliciously signed software update or a forged endpoint certificate could be accepted as genuine before trust is rebuilt on quantum-safe foundations. Either way the point holds against the “just privacy” dismissal: this is an attack on the availability and integrity of market infrastructure, not a data-protection matter, and it is why the migration cannot wait for the machine, even though, unlike harvesting, this channel only opens once the machine exists.

The hardware reality is the counterweight to any sense of imminence.

The estimated physical-qubit cost of factoring a 2048-bit RSA integer has fallen roughly a thousandfold in thirteen years, to under a million in Craig Gidney’s 2025 analysis — and the whole fall is algorithmic and error-correction progress at fixed hardware assumptions, not hardware improving. Yet demonstrated hardware is nowhere close, and the gap is not the one the headlines imply. Industry quotes qubit count, on which Quantinuum’s ninety-four logical qubits look within reach of the fourteen hundred required. But those ninety-four are error-detected — a distance-two code that spots an error and discards the run rather than correcting it and continuing — while the attack needs roughly fourteen hundred error-corrected qubits at code distance near twenty-five, holding integrity through a week of computation. On count and code distance together, every demonstration sits in one corner and the region the attack requires is empty.

The two windows are not the same width. The quantum gap — distance-two detection against distance-twenty-five sustained correction — is wide, plausibly many years. The cyber gap is narrow: the capability exists now, and only operational generalisation is in question. A supervisor faces a fast near-term exposure in Case 1 and a slow but directionally one-sided one in Case 2 — directional not in the sense that Q-Day has a knowable date, which it does not, but that the case for migrating strengthens monotonically as resource estimates fall and embedded dependencies stay hard to inventory. They call for different instruments.

What makes the slow exposure pressing despite the wide window is the migration, not the machine.

Past cryptographic migrations took nine to thirteen years from first warning to broad completion — and those were comparatively easy, near-drop-in replacements for algorithms already known broken. SHA-1’s full federal removal lands in 2030, twenty-four years after the first warning. Post-quantum migration is harder on every axis: larger keys, protocol changes, hardware dependencies, and the unglamorous problem of finding where cryptography is embedded at all. Measured from the 2024 NIST standards, the EU roadmap allows six years to its 2030 high-risk deadline and eleven to full transition in 2035, against a historical base rate north of a decade for an easier task. The honest qualification is that history is a guide, not a forecast: post-quantum migration is also better coordinated, more standardised and more policy-salient than those earlier episodes, which could compress it — or the embedded-cryptography problem could prove worse than any precedent. The base rate frames the risk; it does not settle it.

That a builder of quantum computers is migrating early is the revealed-preference tell, handled carefully. In March 2026 Google set its own internal post-quantum deadline at 2029, ahead of the EU’s high-risk target, citing hardware progress, error-correction advances and the falling factoring estimates. This is not a prediction that a cryptographically relevant machine is near; Google makes none, and neither will I. It is evidence of how much margin a sophisticated actor wants between its defences and a threat it cannot date — conservative private timing under deep uncertainty, not a forecast of Q-Day.

Why the frameworks miss both

The apparatus that should hold these exists and is, on paper, substantial. DORA governs operational resilience and incident reporting; the TIBER-EU regime tests it; the ESRB runs a systemic-cyber framework and a pan-European coordination arrangement for systemic cyber incidents; and the coordinated post-quantum roadmap sets 2026, 2030 and 2035 milestones. Most importantly for the argument here, DORA’s central third-party pillar is already a concentration instrument: the European Supervisory Authorities published their first list of designated Critical ICT Third-Party Providers in November 2025 — nineteen of them, hyperscale cloud, core-banking platforms, data-centre operators — and took direct oversight powers over each, with designation turning explicitly on systemic impact, concentration of reliance, and substitutability. So the framework can see provider concentration, and a piece claiming otherwise would be arguing against its own evidence. But CTPP designation operates at the level of the provider — whether a given critical supplier is systemically important and runs its own house well. It is not built to capture what happens to that provider’s clients together, nor to see the cryptographic layer at all. The gap is not that the framework is blind to concentration. It is narrower, and it lies in two places the CTPP regime does not reach.

The first is the difference between provider concentration and correlated lag — and getting the mechanism right means being precise about where lag actually lives, because not all shared dependencies have it. When a flaw is in a hyperscaler’s managed platform — its hypervisor, a managed database — the provider patches it on the back end and the fix propagates across every client at once, with no client-side action and no window to exploit. That layer concentrates risk but does not lag. The correlated-lag exposure lives in a different layer: distributed software and security agents that each client must deploy itself, and on-premise packages that must be patched one estate at a time. There the same flaw sits exposed across every institution running the dependency, on a correlated clock, during the window before each deploys the fix. The shape of the danger is not hypothetical: the July 2024 CrowdStrike incident, in which a single faulty update to a near-ubiquitous endpoint agent grounded airlines, hospitals and banks within the same hours, was a correlated-failure event through exactly this channel — a shared software dependency, deployed everywhere, failing synchronously. CTPP oversight supervises whether the provider behind such an agent runs its own house well. It does not measure the synchronous exposure of all that agent’s financial-sector clients in the window a frontier-grade flaw is live, because that exposure is a property of the system’s topology rather than the provider’s governance, and it falls between the provider-facing CTPP lens and the firm-facing supervision of each client, seen whole by neither. The second gap is that none of this apparatus has remit over the cryptographic substrate. CTPP criticality is about ICT-service continuity, not about which signature schemes underpin which certificate hierarchies, nor about sequencing a migration so that shared trust anchors do not all reach their deadline unmigrated together. The post-quantum roadmap sets dates but does not own cross-institutional cryptographic concentration. So the formulation is not that no one is looking — it is that provider concentration is supervised, while correlated lag in the distributed-software layer and cryptographic concentration, the two properties that actually synchronise a failure, are currently owned by no single mandate.

That is what makes this macroprudential rather than a pile of firm-level IT problems, and it is a coordination-and-visibility failure across mandates rather than a total blind spot. Firm-by-firm supervision does not, on its own, reliably reveal a system-wide exposure: each institution inventories its own dependencies, tests against its own scenarios, and migrates its own cryptography on its own schedule, and the property that matters — concentration plus correlated lag across the whole estate — is the one no single filing contains. The framework already knows this shape from funding markets. It has built half the apparatus to see it in the substrate, in the CTPP regime, and not yet the half that would catch the synchronous failure.

What a supervisor should measure differently — and what would prove me wrong

The practical content is not a forecast. It is a sequence, and the order matters, because the obvious objection to everything above is fair: if this is really macroprudential, where is the operational equivalent of a capital buffer or a liquidity coverage ratio — the hard instrument, not another reporting form? The answer is that the instruments exist in adjacent form and the binding constraint on using them is measurement. A liquidity coverage ratio was possible only once liquidity could be measured against a defined stress; the buffer came after the metric, not before. The substrate has no agreed metric yet, which is why the first asks are measurement asks — not as a substitute for hard tools, but as their precondition.

So, in order. First, require threat-led tests to record the realism gap they now carry: a TLPT attestation should state whether the red team had access to frontier-grade offensive tooling comparable to the assessed threat, so a certification of detection is read against a known adversary level rather than an unstated one. Second — the prescriptive one — require the ESRB’s systemic-cyber scenarios to carry an explicit autonomous-capability parameter and, for the quantum channel, a code-distance-progress assumption, with a public justification when either is omitted; operationally this means the scenario-design committee adds two named variables to an existing process rather than inventing a new exercise. Third, extend the CTPP regime’s concentration lens from the provider to the correlated-lag exposure of its clients in the distributed-software layer: cross-institutional dependency inventories and cryptographic inventories, the latter tagged by confidentiality duration and signature dependency, held by the authority whose mandate is the system rather than the firm.

And then the direction hard instruments would take — named so the thesis is not just dashboards, but flagged as direction rather than ready policy, because the trade-offs here are real and partly adverse. Once correlated-lag exposure is measurable, the analogue to a large-exposure limit is an operational concentration limit — a ceiling on how much of a critical function the system routes through a single dependency. The honest objection is that infrastructure is not fungible the way capital is: you cannot tell a bank it has “hit its hyperscaler limit” without telling it to stop, and a naive mandate to run core systems actively across two clouds can worsen resilience by doubling the attack surface and multiplying configuration error. So the feasible version is not forced active multi-provider; it is measured concentration thresholds that trigger heightened oversight and tested exit and fallback capability — closer to a supervisory add-on than a hard cap — and it applies most cleanly to the distributed-software layer where substitutability is real, not to the hyperscale oligopoly where it largely is not. The point of leading with measurement is that which of these is even feasible, and where, cannot be known until the concentration-plus-lag exposure is quantified. A limit set against an unmeasured exposure is arbitrary, and arbitrary limits are how good instruments get discredited.

And the kill criteria, because a piece arguing for supervisory attention should say what would retire the argument — in metrics a supervisor can actually read. The thesis weakens materially if a tracked frontier-model evaluation against hardened, actively defended environments (not benchmark ranges) shows the capability failing to generalise; if the share of tier-one institutions’ critical services concentrated in a handful of designated providers turns out low rather than high once the CTPP registers are mapped against each other; if post-quantum migration progress, measured against the historical nine-to-thirteen-year baseline, runs ahead of rather than behind schedule; or if the empty region in the logical-qubit chart stays empty while access to offensive models diffuses widely. Each is discrete and reportable. If they come back reassuring, the right conclusion is that the framework was adequate and the substrate belonged in the engineering domain after all.

The summary is plain. Two correlated exposures surfaced in 2026 that the resilience framework does not yet hold as stability concerns — one live and uncertain, one slow and directionally one-sided — and both turn systemic through a property the framework half-sees: it supervises provider concentration through the CTPP regime, but not the correlated lag or the cryptographic concentration that would actually synchronise a failure. In Case 1 the supervisor’s window is narrow and may be closing as the capability generalises or diffuses. In Case 2 it is wide, but the migration clock inside it is already short against the historical base rate. The cost of recognising this late is specific and not abstract: a single flaw in a shared dependency detected across the estate in the same week, or trust in a common certificate hierarchy failing closed during a stress window, is exactly the correlated event prudential supervision exists to prevent — and the one the substrate is currently arranged to produce. The instruments to measure it are a scenario parameter and a register away. The instruments to limit it are the ones the framework already owns, pointed at a layer it has not yet pointed them at. What is missing is not the tools but the decision to treat the substrate as load-bearing before the event that proves it was.

Paweł Fiedor — The Macro Prudential View

The views expressed are the author’s own and do not necessarily reflect those of any institution with which the author is or has been affiliated.

Sources: Anthropic, Project Glasswing announcement and Claude Mythos Preview, 7 April 2026 — https://www.anthropic.com/glasswing; UK AI Security Institute, Our evaluation of Claude Mythos Preview’s cyber capabilities, April 2026 — https://www.aisi.gov.uk/blog/our-evaluation-of-claude-mythos-previews-cyber-capabilities; UK AI Security Institute, Our evaluation of OpenAI’s GPT-5.5 cyber capabilities, April 2026 — https://www.aisi.gov.uk/blog/our-evaluation-of-openais-gpt-5-5-cyber-capabilities; Wall Street Journal, White House Opposes Anthropic’s Plan to Expand Access to Mythos Model, 30 April 2026 — https://www.wsj.com/tech/ai/white-house-opposes-anthropics-plan-to-expand-access-to-mythos-model-dc281ab5; Bloomberg, reporting on the reported private-forum access leak, April 2026 — https://www.bloomberg.com/news/articles/2026-04-21/anthropic-s-mythos-model-is-being-accessed-by-unauthorized-users; Bloomberg, Anthropic to Give Mythos Access to EU Cybersecurity Agency ENISA, 1 June 2026 — https://www.bloomberg.com/news/articles/2026-06-01/anthropic-to-give-eu-s-cybersecurity-agency-access-to-mythos; Eurogroup, statement following the meeting of 4 May 2026 — https://www.consilium.europa.eu/en/meetings/eurogroup/2026/05/04/; Mandiant, M-Trends 2025 (global median dwell-time series, 2011–2024) — https://cloud.google.com/security/resources/m-trends; Mandiant, M-Trends 2026 (2025 dwell-time figure) — https://cloud.google.com/security/resources/m-trends; Epoch AI, frontier-models database and Can AI Scaling Continue Through 2030? — https://epoch.ai/data/notable-ai-models and https://epoch.ai/blog/can-ai-scaling-continue-through-2030; International Energy Agency, Energy and AI, April 2025 — https://www.iea.org/reports/energy-and-ai; DeepSeek-AI, DeepSeek-V3 Technical Report, arXiv:2412.19437 — https://arxiv.org/abs/2412.19437; C. Gidney, How to factor 2048-bit RSA integers with less than a million noisy qubits, arXiv:2505.15917 (2025) — https://arxiv.org/abs/2505.15917; C. Gidney and M. Ekerå, How to factor 2048-bit RSA integers in 8 hours using 20 million noisy qubits, Quantum 5:433 (2021) — https://quantum-journal.org/papers/q-2021-04-15-433/; Quantinuum, Helios system results, March 2026 — https://arxiv.org/abs/2602.22211; Google Quantum AI, Quantum error correction below the surface code threshold (Willow), Nature, December 2024 — https://www.nature.com/articles/s41586-024-08449-y; Harvard/QuEra et al., Logical quantum processor based on reconfigurable atom arrays, Nature, December 2023 — https://www.nature.com/articles/s41586-023-06927-3; NIST, post-quantum cryptography standards FIPS 203/204/205, August 2024 — https://csrc.nist.gov/projects/post-quantum-cryptography; NIS Cooperation Group, Coordinated Implementation Roadmap for the Transition to Post-Quantum Cryptography, 2025 — https://digital-strategy.ec.europa.eu/en/library/coordinated-implementation-roadmap-transition-post-quantum-cryptography; Google, A timeline for post-quantum cryptography migration, 25 March 2026 — https://blog.google/innovation-and-ai/technology/safety-security/cryptography-migration-timeline/; European Supervisory Authorities (EBA, EIOPA, ESMA), first designation of Critical ICT Third-Party Service Providers under DORA, 18 November 2025 — https://www.eba.europa.eu/publications-and-media/press-releases/european-supervisory-authorities-designate-critical-ict-third-party-providers-under-digital; ESRB, systemic-cyber framework and EU-SCICF — https://www.esrb.europa.eu/news/pr/date/2022/html/esrb.pr.220127~f1548f677e.en.html; S. Hossenfelder, video commentary on quantum computing and cryptanalysis, 2025–26 — https://www.youtube.com/watch?v=N-9muK0mv5w&pp=ygUbc2FiaW5lIGhvc3NlbmZlbGRlciBxdWFudHVt & https://www.youtube.com/watch?v=qV7hQEtr3ic&t=2s&pp=ygUbc2FiaW5lIGhvc3NlbmZlbGRlciBxdWFudHVt. Chart data as cited in each figure; dwell-time series from M-Trends as above; logical-qubit and code-distance points from the Gidney, Quantinuum, Google and QuEra sources above.

On 11 May the European Commission delivered its report on the functioning of the Money Market Fund Regulation. The EU’s €1.95 trillion sector, it found, has grown by close to half since 2019 and came through both the March 2020 dash for cash and the 2022 gilt crisis without a single fund gating or suspending redemptions. Funds hold liquidity comfortably above the regulatory minima. The appropriate response, the Commission concluded, was not to reopen the Regulation but to set a non-binding supervisory benchmark: weekly liquid assets of around 40% for the stable-value funds, against a binding floor of 30%.

On 14 May, HM Treasury and the FCA confirmed the opposite instinct. Having consulted on this since 2023, the UK announced it will legislate to raise its binding liquidity requirements and, more consequentially, to sever the regulatory link between a fund’s liquidity level and the tools that let it slow or stop redemptions. The new regime is expected to be in place by the end of 2026.

The two documents describe the same instrument, draw on the same two crises, and read off much the same data; they reach opposite conclusions about what to do.

There is a third party to the disagreement, and it had already cast its vote. Fifteen months earlier, in February 2025, the European Systemic Risk Board graded the Commission materially non-compliant with the recommendations it had issued in 2021 on precisely this question. The assessment was neither gentle nor fringe: the team included Richard Portes and was chaired from within ESMA. On three of the four headline recommendations — the ones that would have changed the funds’ structure and their liquidity — the Commission had taken no action, and its justifications were judged insufficient.

That grade measured the Commission’s response against the ESRB’s recommendations: it records that the action fell short of what was asked, not that the sector failed a test. Even read that narrowly, it means the Commission reached its reassurance over the objection of the authority it sits beside on systemic risk, on a reform agenda that authority still judges unfinished. Working out who has the better of it means being precise about what a liquidity buffer measures, and what lies beyond its reach.

A short word on the LVNAV

European regulation offers three kinds of money market fund. Public-debt constant-NAV funds hold government paper and maintain a fixed share price. Variable-NAV funds let their price float with the value of their assets. Between them sits the low-volatility NAV fund, the LVNAV, which is the one that matters here and the largest single category in Europe at roughly 46% of the sector.

The LVNAV is a hybrid by construction. It values its assets at amortised cost and rounds its share price to a stable €1.00, but only while its true mark-to-market value stays within twenty basis points of par. Step outside that collar and the fund must price at its real value, like a VNAV. The stability is therefore conditional, and the condition is invisible to the investor until the moment it fails. That is the feature corporate treasurers pay for: cash that looks and settles like a deposit. It is also where the fragility sits. The Commission understood as much once — its own 2013 impact assessment warned that a constant share price “triggers false incentives and exacerbates runs.”

Why a money fund runs

The collar builds in a cliff. A fund whose assets are quietly losing value still transacts at €1.00, right up to the twenty-basis-point edge, at which point the price drops to meet reality. An investor who redeems while the fund is inside the collar gets out at par. An investor who waits until it breaks absorbs the loss the early movers left behind. The collar holds the price flat and then moves it in a single step, so the deterioration that a floating fund would show gradually arrives here all at once.

The Regulation adds a second cliff beside the first. When a fund’s weekly liquid assets fall below 30%, its board is obliged to consider imposing fees or redemption gates. The trigger is discretionary, not automatic. But investors do not need it to be automatic; they need only to anticipate it. Watching the buffer approach 30%, a holder knows a breach may bring restrictions, so the moment to leave is before the threshold is reached, while redemptions still clear freely and at par. The discontinuity that matters is in the behaviour, not in the text of the rule.

Put the two together and the redemption decision becomes a coordination game with two equilibria, one of them bad.

If you expect other investors to sit tight, you sit tight too: the fund holds at par, you keep the yield, and redeeming would only cost you a little of it. If you expect them to run, the calculation inverts, and redeeming becomes the one way to get out at par, ahead of the step and ahead of any gate. Holding and running are both equilibria, and which one obtains depends on what each investor believes the others will do.

The fragility is in the second equilibrium. The calm one holds only while everyone trusts that it will hold. Any event that shifts enough investors toward expecting a run makes running the correct response for each of them individually, and the expectation then confirms itself. The collar and the threshold are what give the run its edge, because they put a discrete prize on being early: exit at par, before the step. This is the first-mover advantage the ESRB identified in 2021. It does not require panic or misjudgement; it follows from the payoffs.

There is a corollary the Commission’s own evidence supports and its conclusion passes over. If drawing on a buffer is what signals distress and trips the threshold, managers will be reluctant to draw on it. The ESRB found exactly this when it examined March 2020: funds suffered heavy outflows but did not run their weekly liquid assets down to match, which the assessors read as “low levels of usability” for the buffers. A buffer that a manager will not spend, for fear that spending it invites the run, is worth less in an event than its headline size suggests.

The constraint outside the fund

The report measures resilience as a fund’s ability to meet redemptions out of its own liquid assets without forced selling. On that measure the sector looks sound, because funds do hold liquidity well above the minima. The measure is a single-fund one, though, and money funds are tested by system-wide events: in a stress, every fund holds similar paper and reaches for cash at the same moment.

Start with how a fund actually raises that cash, because the intuitive version of the short-side argument goes wrong here. Weekly liquid assets are not mostly a stock of sellable securities; they are largely paper maturing within the week. A fund under redemption pressure meets it first by letting that paper mature and collecting the proceeds, and by declining to reinvest. It does not have to sell commercial paper into a thin market to find the cash. For the individual fund, the buffer works more or less as designed.

The strain does not disappear; it moves to the issuer. When a money fund collects its maturing paper and declines to roll, the issuer that sold that paper — a bank or a large corporate funding itself week to week — has to refinance somewhere else. The natural buyers of the new paper are money funds, and in a system-wide event they are all doing the same thing at once: husbanding cash rather than extending it. So the issuer cannot roll at the old size or the old price. The pressure the fund relieved on its own balance sheet reappears on the issuer’s, at the rollover margin. And it does not stay wholly on the issuer’s side. A fund meets this week’s redemptions from maturing paper, which pays at par, so the buffer does its job there. The credit strain lands instead on the same issuer’s longer-dated paper, still on the fund’s books: it reprices as the issuer’s spread widens, and in the extreme, if the issuer defaults, even maturing paper stops paying in full. That is what moves the shadow NAV toward the collar. Holding more weekly liquid assets reduces this exposure, since it leaves a smaller spread-sensitive long book, though it does nothing for the dealer-capacity limit that decides whether the issuer can refinance at all. None of this puts issuer-side strain in a separate regulatory silo: it returns to the funds through their own asset marks.

Dealers are meant to bridge exactly this kind of gap, standing in to buy paper that cannot immediately be placed. Their capacity to do so is fixed in the short run by leverage and capital rules, and when the whole sector turns at once it is quickly exhausted. Price impact becomes severe, and at the margin some issuance cannot be placed at a price the issuer can pay. The adjustment then runs through quantities — issuance abandoned, rollovers refused — and not through price alone. A fund’s weekly liquid assets tell you whether that fund can find cash. They tell you nothing about whether the market can absorb every fund finding cash together. Raising every fund’s buffer improves the first and relocates the second rather than resolving it: each fund is individually safer, while the aggregate strain shifts onto issuers and a dealer sector that cannot grow to meet it. A higher buffer changes the timing and size of that strain; it does not create the capacity to absorb it.

None of this is new, and the piece is better for not pretending otherwise. The role of dealer balance-sheet capacity as the binding constraint on absorbing forced sales, with quantity rationing taking over from price once that capacity is reached, is the standard reading of the 2020 dash for cash. The Financial Stability Board’s Holistic Review of the March Market Turmoil set it out at the official level in November 2020, and it runs through the central banks’ own accounts of why they intervened and the wider market-based-finance literature. The Federal Reserve stood up two facilities in March 2020, not one: a money market fund liquidity facility to take funds’ assets, and a commercial paper facility to backstop issuance. Both channels had seized — the fund-level and issuer-level constraints are one constraint seen from two ends.

The Commission sees this. Its report accepts that dealer liquidity provision is more constrained and less responsive than before 2008, characterises much of the problem as external to the funds, and points to the right remedies: deeper short-term funding markets and access to central-bank facilities. Having located the binding constraint outside the Money Market Fund Regulation, it concludes that the Regulation itself needs no substantive change. That is where the diagnosis and the conclusion stop fitting together. An external constraint is a reason a fund-level buffer cannot fix the system; it is not a reason to leave every other lever untouched, including the levers, such as the run-inducing threshold and the stable share price, that sit squarely inside the Regulation. This is not a call for a bigger buffer to do a buffer’s impossible job. A higher, usable floor buys fund-level resilience while the systemic gap still needs the external tools the Commission names; the complaint is that the Commission declined the structural levers it did control and answered with a benchmark no fund is obliged to meet.

Three regimes, three answers

Set the three big regimes beside each other and the EU’s choice looks lonelier than its report admits.

The United States went first and went furthest. In 2014 the SEC required institutional prime and institutional municipal funds — the ones most prone to run — to abandon the stable share price and float their NAV, a change that took effect in 2016. It removed the deposit illusion from the funds where it was most dangerous. Then in 2023, in response to March 2020, it raised weekly liquid assets to 50% and daily to 25% across the board, and cut the automatic link between breaching a liquidity threshold and imposing fees. The American settlement is a floating price for the riskiest funds and high, usable buffers for the rest.

The United Kingdom proposes to keep the stable-value structure and the collar but to raise weekly liquid assets toward 50% and to sever the link between the liquidity threshold and the redemption tools. The FCA’s reasoning is explicit: a 40% requirement would not cover the largest plausible sterling outflows, 50% would, and a dash-for-cash event of the 2020 kind would call for 60 to 70%. The effect is to make the buffer both higher and usable, so that a fund can spend it without that act alone triggering the restrictions that begin the run.

The EU’s answer is a binding floor it left untouched at 30%, a non-binding benchmark of 40%, and one genuine reform: the requirement, delivered through the 2024 overhaul of the AIFMD and UCITS directives rather than the MMFR itself, that funds make at least one liquidity-management tool available. That reform is real, and it is the single ESRB recommendation the Commission was graded as having substantially met. It is also the cheapest of the four. The two costly ones, floating the LVNAV and raising binding liquidity, it declined.

The bars are not strictly like-for-like, and the chart’s footnote says so: the regimes define liquid assets differently, and the ESRB’s 45% is a composite that counts public-debt holdings the others treat separately. The ranking survives the caveat. The EU’s binding floor is the lowest of the group, and the one number it added is the only one in the field that no fund is obliged to meet.

The benchmark that binds no one

Return to the 40% benchmark, because it is the centre of the Commission’s actual policy. Two things about it matter.

The first is that it is not binding. It is a supervisory expectation, not a regulatory minimum, so a fund that sits below it has breached nothing and owes no remediation. In the legal sense the benchmark binds no one, which is the sense the title of this piece intends.

The second is where the level sits. Forty per cent is the level the FCA examined and rejected as too low for the largest sterling outflows; both are pure weekly-liquid-asset figures, so that comparison is like-for-like. It is also at or below where the weakest quarter of EU low-volatility funds has held its liquidity through much of the past five years. The 25th percentile ran through the mid-40s for most of 2020 to 2023, touched 40% as early as the third quarter of 2021, and has sat in a narrow band straddling the 40% line since the start of 2024.

On the Commission’s own chart the 25th percentile reaches 39% in the second quarter of 2025, the only quarter in the five years plotted in which it falls below 40% outright. The report’s text says the figure never fell below 40%; the chart a couple of pages on shows 39%. The discrepancy itself is minor. The 25th percentile sits exactly on the 40% line in four other quarters and has stayed within a point or two of it since the start of 2024, so a binding 40% floor would have bound on part of the weakest quartile across much of the recent period rather than in one isolated quarter. A non-binding version of it, pitched at that level, describes where the sector already operates rather more than it disciplines it.

That is the substance of the objection. The ESRB asked for four things in 2021: make the LVNAV’s price fluctuate, repeal the threshold that manufactures the first-mover advantage, raise binding liquidity, and improve the data on who holds what. Against that list, a non-binding number pitched where the weakest quartile already sits falls well short of a reform, which is the reading the ESRB itself recorded when it graded the response.

What the Commission gets right

The honest objection to all of this is that the Commission is not simply wrong, and the argument is stronger for saying so.

The stress in money funds is not spread evenly across the sector. It concentrates in a tail. And the tail is exactly where the coordination game described earlier actually fires. A run needs a correlated investor base — holders who will reach for the exit on the same signal at the same time. Funds with diversified, operational cash investors do not supply one; funds whose investors are a single strategy, or a single type all exposed to the same shock, do.

The 2022 gilt crisis showed the pattern. The median sterling LVNAV saw a one-week net outflow of around 9% — heavy for a cash vehicle, but well inside the liquidity the rules require it to hold, and several funds with diversified cash-management investors took money in over the same weeks. The damage was concentrated in a small set of funds used as collateral vehicles by liability-driven investment strategies, whose investor base was about as correlated as an investor base can be. The worst one per cent lost more than a third of their assets in a single week. The weekly liquidity rules are sized to a week of stress, so the comparison is a fair one: a one-week outflow above a third of assets exceeds the 30% the rules require a fund to hold in total, which means that for those funds the buffer would have been fully spent and the fund still short. March 2020 had the same shape — most LVNAVs saw modest outflows while a small fraction of US dollar funds lost over 30% of their assets in a week. The European sector is not a bystander to this. Its own correlated tail is the US-dollar-denominated prime and LVNAV funds concentrated in Ireland and Luxembourg, held by investors who cluster by currency and mandate; that segment carried the 2020 strain on the European side, and it sits inside the EU rules.

A tail problem is a poor match for a sector-wide instrument. Raising the floor on every fund to reach a concentrated minority charges the prudent majority for resilience they already carry, and leaves the concentration that creates the tail untouched. The Commission’s wariness about a blanket increase has a real argument behind it, and the LVNAV does serve a cash-management function for which, in its words, there is “no obvious economic alternative.”

The trouble is that this argument points to a different policy, not to none. If the danger lives in particular funds with particular investor structures, the response is to find and constrain them: concentration and investor-type limits, granular data on who holds what, and buffers a manager can actually draw down under stress without that act alone starting the run. The first two are close to the monitoring and reporting recommendation the ESRB made and the Commission declined; the third is the core of the UK reform. The case against a blunt floor is a case for sharper tools; the Commission adopted neither.

What the resilience rests on

There is a reason the Commission can read the same record as reassuring where the ESRB reads a deferred problem.

In March 2020, and again in the 2022 gilt episode, the constraint that would otherwise have bound was relieved from outside, though by different routes. In 2020 the ECB’s pandemic asset purchases — and, for the EU’s dollar funds, the Federal Reserve’s facilities — stood behind short-term funding directly, at the moment dealer capacity ran out. In 2022 the Bank of England’s gilt intervention worked a step upstream: buying long-dated gilts broke the margin spiral that was forcing liability-driven investors to sell, which stopped the redemptions draining the sterling money funds. Either way a public balance sheet stood in where private capacity had run out, and no EU fund had to gate. That is the fact the Commission leans on. What the record cannot show is how the funds would have fared without those interventions, because the interventions are the reason the counterfactual never ran.

This is the part the Commission half-states when it lists central-bank facilities among the answers. The resilience it observes is real, but it is conditional, and the condition is not priced. An LVNAV offers its investors something close to a bank deposit — a stable value, settlement like cash — at a yield above a deposit. A bank that offers a deposit pays for the public backstop behind it through deposit-insurance premiums, capital requirements, and supervised access to the central bank’s standing facilities. The LVNAV has been able to rely on public support in stress — less formal than deposit insurance, and discretionary rather than guaranteed — while carrying none of those costs. That specific gap, rather than the general truth that all liquidity transformation ends somewhere at the central bank, is what the report leaves unaddressed.

Providing the LVNAV with that implicit backstop may well be the right policy. It is defensible if it is acknowledged, and if the implied support is either priced or contained by the kind of structural limits the ESRB asked for. It is harder to defend when the support is read as evidence of the funds’ own soundness, because it is discretionary: the willingness to deploy it again, at the same scale, may not be there when it is next needed. That is the gap the ESRB chair pointed to in urging the European Parliament’s economic committee, last December, not to wait for the next crisis to settle the framework. The Commission’s report establishes that the funds met their redemptions. It is quieter on what allowed them to.

Paweł Fiedor — The Macro Prudential View

The views expressed are the author’s own and do not necessarily reflect those of any institution with which the author is or has been affiliated.

Sources: European Commission, Report on the functioning of Regulation (EU) 2017/1131 on money market funds, COM(2026) 350 final, 11 May 2026 — https://ec.europa.eu/finance/docs/law/260511-money-market-funds-report_en.pdf; HM Treasury and Financial Conduct Authority, money market fund reform announcement, 14 May 2026 — https://assets.publishing.service.gov.uk/media/6a059b2622977ebc82cb3f5d/The_Government_and_FCA_announce_plans_to_reform_UK_Money_Market_Fund_Regulations..pdf; European Systemic Risk Board, Recommendation ESRB/2021/9 on the reform of money market funds — https://www.esrb.europa.eu/pub/pdf/recommendations/esrb.recommendation220125_on_reform_of_money_market_funds~30936c5629.en.pdf; European Systemic Risk Board, assessment of compliance with Recommendation ESRB/2021/9, February 2025 — https://www.esrb.europa.eu/pub/pdf/recommendations/esrb.compliancereport202502_1~cfa5aff4bd.en.pdf; Regulation (EU) 2017/1131 on money market funds (MMFR) — https://eur-lex.europa.eu/eli/reg/2017/1131/oj/eng; European Commission, impact assessment accompanying the 2013 money market funds proposal — https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52013SC0315; Directive (EU) 2024/927 (AIFMD II), amending the AIFMD (2011/61/EU) and the UCITS Directive (2009/65/EC) to require liquidity-management tools — https://eur-lex.europa.eu/eli/dir/2024/927/oj; Financial Conduct Authority, CP23/28, Updating the regime for Money Market Funds — https://www.fca.org.uk/publications/consultation-papers/cp23-28-updating-regime-money-market-funds; U.S. Securities and Exchange Commission, Money Market Fund Reforms, Release No. 33-11211 (2023) — https://www.sec.gov/files/rules/final/2023/33-11211.pdf, and the 2014 institutional prime and municipal floating-NAV reforms — https://www.sec.gov/newsroom/press-releases/2014-143; Financial Stability Board, Holistic Review of the March Market Turmoil, 17 November 2020 — https://www.fsb.org/2020/11/holistic-review-of-the-march-market-turmoil/; Federal Reserve, Money Market Mutual Fund Liquidity Facility and Commercial Paper Funding Facility, March 2020 — https://www.federalreserve.gov/monetarypolicy/mmlf.htm; European Central Bank, Pandemic Emergency Purchase Programme, March 2020 — https://www.ecb.europa.eu/mopo/implement/pepp/html/index.en.html; Bank of England, gilt market operation announcement, 28 September 2022 — https://www.bankofengland.co.uk/news/2022/september/bank-of-england-announces-gilt-market-operation; Bank of England, Financial Stability Report, July 2023 — https://www.bankofengland.co.uk/financial-stability-report/2023/july-2023; European Systemic Risk Board, chair’s remarks to the European Parliament Committee on Economic and Monetary Affairs, December 2025 — https://www.europarl.europa.eu/doceo/document/P-10-2025-004833_EN.html. Data: regime liquidity requirements per the regulatory sources above; the 25th-percentile and cross-sector-average weekly-liquid-asset series read from COM(2026) 350 final, sterling LVNAV redemption data for the 2022 gilt episode — https://ec.europa.eu/finance/docs/law/260511-money-market-funds-report_en.pdf.

On 2 April 2025, the US administration announced a wall of tariffs, and the market did what markets do when the rules of global trade are rewritten overnight. The VIX spiked to 52 — its second-highest intraday peak since the COVID crash. Treasury volatility, measured by the MOVE index, jumped to levels last seen during the 2023 banking crisis. European equity volatility followed. For a few days the screens looked the way they look before a central bank picks up the phone.

And then nothing happened. No emergency facility. No unscheduled meeting. No statement promising to do whatever it takes. The Federal Reserve, which was at that moment still shrinking its balance sheet, carried on shrinking it. The market repriced, found a level, and moved on.

This is the kind of episode that invites a comforting story. The comforting story goes like this: modern markets are electronic, deep, and fast; algorithmic market-makers provide liquidity continuously and reprice risk in milliseconds; we have, through some combination of technology and hard-won experience, built markets that absorb shocks on their own. Two wars and a trade war in four years, and the system held. Perhaps the machines have made us anti-fragile.

I want to take that story seriously, because a version of it is true. But the cleaner reading of the evidence is that it is incomplete about why — and getting the why wrong has real consequences for anyone whose job is to keep the system standing.

The calm is selective

Start with the texture of the last few years, because “markets were calm” is too coarse a claim to be useful.

The point is not that one market was calm and another wild. It is that “the system” is not one thing. Each of these markets has its own microstructure, its own participants, its own plumbing — and they broke, or didn’t, for different reasons. The shock that froze the gas market in 2022 left equities largely untouched; the shock that drove the MOVE index to a banking-crisis high in March 2023 was a banking crisis, not a vol event. If we want to know whether markets have become more resilient, we have to ask the question market by market, mechanism by mechanism — not wave at an index and call it calm.

It is worth holding one distinction in mind from the outset, because the whole argument turns on it. There is a difference between a repricing shock — where asset prices move violently as the market digests new information — and a funding shock, where the problem is not the level of prices but the inability to finance positions at any price. The two can look similar on a volatility chart. They are not similar in the plumbing, and as we will see, that difference is what separates a market that bends from one that breaks.

A decade of rising rescues

Here is the fact that the comforting story has to explain away.

For most of the post-crisis period, the official sector was called in with rising frequency. The chart above plots the major liquidity-event episodes since 2010 — the 2010 Flash Crash, the October 2014 Treasury flash rally, the August 2015 ETF dislocation, the 2016 sterling flash crash, 2018’s “Volmageddon,” the September 2019 repo spike, the March 2020 Treasury dysfunction, the 2022 LME nickel suspension and retroactive trade cancellation, the September 2022 gilt/LDI doom loop, the March 2023 banking failures, and the August 2024 yen carry unwind — and beneath them, the cumulative count of episodes that drew an official response.

The line steepens. Six events in the first decade; five more in the four years after. And the nature of the response escalated alongside the frequency. The early episodes drew rule changes — circuit breakers after the Flash Crash, reporting requirements after 2014, product delistings after Volmageddon. No public money. From 2019 onward, every episode drew the balance sheet: emergency repo operations, unlimited quantitative easing, the Bank of England’s gilt purchases, all deposits backstopped at Silicon Valley Bank, the Swiss authorities’ rescue of Credit Suisse. The system moved from adjusting the rules to deploying the central bank’s own balance sheet. That is a meaningful escalation, and it is the part of the record that should make anyone cautious about declaring victory.

And then — the cumulative line goes flat. After the March 2023 banking crisis, three shocks of comparable scale arrived, and none of them drew a backstop. The yen carry unwind in August 2024, which sent the Nikkei down 12.4% in a single session — its largest one-day fall by points in history — drew nothing more than verbal guidance from the Bank of Japan. Liberation Day in April 2025 drew nothing. The Iran/Hormuz shock in February 2026 drew nothing. Three loud shocks, no balance sheet.

I have classified the yen carry episode as “absorbed” rather than as an intervention, and that is a judgement worth defending openly. The Bank of Japan did say something — its deputy governor signalled that the Bank would not raise rates while markets were unstable. But it committed no public balance sheet, opened no facility, and bought nothing. For a chart whose vertical axis is the deployment of official liquidity, jawboning belongs on the “absorbed” side of the line. A purist could disagree; I have noted it rather than hidden it.

What the central bank had to do — and didn’t

The intervention timeline makes a claim; the cleanest way to test it is to look at the backstop itself.

The chart above shows the weekly change in the Federal Reserve’s Treasury holdings during two windows, on a single shared scale. The left panel is the spring of 2020. The bars climb a wall: the Fed added more than $360 billion to its Treasury portfolio in a single week, and roughly $1.7 trillion over a few months, simply to keep the market clearing. This was not stimulus. It was plumbing — the central bank becoming the buyer of last resort because private dealers could no longer absorb the flood of selling.

The right panel is the spring of 2025, on the same axis. It is almost flat. Through Liberation Day, the largest weekly move is a reduction of about eighteen billion dollars — because the Fed was running quantitative tightening, draining its balance sheet at a deliberate, pre-set pace, and a market shock that would once have hijacked monetary policy did not so much as interrupt the runoff. The Treasury runoff cap had been reduced to $5 billion a month from April 2025; the balance sheet was barely moving by design, and the shock did not change that. (Runoff finally ceased entirely on 1 December 2025, for reasons that had nothing to do with any acute event.)

That contrast is the argument. In 2020, the shock forced the central bank to reverse course violently. In 2025, a comparable shock did not register as a reason to pause a trickle — not because the stress wasn’t real, but because nothing about it required a balance-sheet response.

It is worth pausing on just how deep the 2020 dysfunction ran, because it sets the bar for what “the plumbing breaking” actually looks like. In normal times the New York Fed transacts in a narrow band of liquid, on-the-run Treasury issues — a few dozen distinct securities on a busy day. In the dash-for-cash of March 2020, that number exploded to more than 250 distinct securities in a single day. The Fed was not fine-tuning; it was buying across the entire curve, absorbing the old, illiquid, off-the-run issues that dealers would no longer hold. The breadth of what the central bank had to hold is itself a measure of how completely private intermediation had seized. (This is a 2020-only series — the transaction-level data is released with a two-year lag — so it cannot speak to the recent episodes. It is here as a yardstick for the depth of genuine dysfunction, not as part of the resilience comparison.)

The shape of a market that bent without breaking

So the recent shocks were absorbed. But “absorbed” can mean two very different things, and the distinction matters enormously. It can mean the shock was small. Or it can mean the shock was real and the market took it without seizing. Gas is the cleanest place to see the difference, because Europe has now been hit twice.

The chart above tracks the Dutch TTF gas benchmark — front-month price on top, open interest (the number of outstanding futures contracts, a proxy for how many participants are actually in the market) below. In 2022, the price reached €339 per megawatt-hour, and open interest collapsed — falling 54% from its pre-invasion peak to its trough. This is what a participation crisis looks like: as prices and margin requirements spiralled, leveraged hedgers could no longer fund their positions and were forced out of the market precisely when hedging was most valuable. The market didn’t just get expensive; it got thin, shedding the very participants who give it depth.

By February 2026, gas prices roughly doubled on the Iran/Hormuz shock — a sharp move, peaking near €62. But look at the open interest. It barely flinched. Participation fell only about 23% from what was, by then, an all-time high — a high more than four times the 2022 trough. A larger relative price move, from a vastly higher base of participation, produced less than half the dislocation. The 2026 decline was an orderly de-risking from a record high, not a margin-driven exodus. The market bent. In 2022, it had broken.

I think this is the single most important contrast in the whole picture, and it generalises. The question is never simply “how big was the shock?” It is “did the shock force participants out of the market, or did they choose to step back and then return?” The first is dysfunction. The second is resilience. And the difference between them lives in the plumbing — in margin, in clearing, in who is obligated to keep providing liquidity when it stops being profitable to do so. This is not a parochial commodities concern: when a margin spiral forces hedgers out of a cleared futures market, the strain runs straight through the clearing house to its members, and a commodity dislocation becomes a systemic one — which is precisely the channel the gilt crisis exposed in a different market months later.

Where the dysfunction lived

If resilience lives in the plumbing, it is worth asking where, exactly, the 2022 dysfunction concentrated — because the answer turns out to complicate the obvious “European energy crisis” reading.

The chart above indexes open interest across four gas benchmarks to January 2022. Three of them collapsed together through 2022: the Dutch TTF (continental Europe), the UK’s NBP, and — crucially — Asia’s JKM. The fourth, North American gas, did not move. It sat flat through the entire period while the other three lost between 44% and 60% of their participation.

The obvious story — that this was a European energy crisis — does not survive that fourth line. JKM is an Asian benchmark; if the dysfunction were geographic, it should not have collapsed in lockstep with the European hubs. What the three falling benchmarks share is not geography. It is that they are the LNG-linked contracts, traded by a globally mobile set of participants — utilities, commodity trading houses, LNG portfolio players — who hedge across all of them at once. When a price and margin spiral in one drained the collateral those participants had available, it drained their capacity to hold positions in the others. North American pipeline gas, with its different and more domestic participant base, was insulated.

There is a further pattern worth flagging, though I want to be careful not to overclaim it. The three benchmarks that collapsed all clear at the same central counterparty — ICE Clear Europe — while North American gas clears elsewhere. That is consistent with a story in which procyclical margin models at a shared clearing house amplified the contraction across all the products it cleared. But it is also consistent with the simpler explanation that these markets just share participants. The data here cannot separate the two, and I would treat the clearing overlap as an intriguing pattern that deserves investigation rather than a settled mechanism. Either way, the lesson is the same: the dysfunction respected the boundaries of participants and plumbing, and ignored national ones — which is exactly why a venue-by-venue regulatory perimeter can miss it.

Two kinds of liquidity

We can now name the thing the comforting story gets wrong. It assumes that the liquidity you see in calm markets is the liquidity you will have in a crisis. It is not.

There are, roughly, two kinds of people providing liquidity in a modern market. The first are committed dealers — banks, intermediating on their own balance sheets, backed by capital and bound by obligation and regulation. In calm markets they are present but capital-constrained; they do not provide the tightest prices. In stress they retrench and widen their quotes, but they stay in the book. They degrade gracefully.

The second are what the microstructure literature calls endogenous market-makers — the principal trading firms and high-frequency market-makers whose capital is uncommitted. In calm markets they are abundant: they provide the tightest spreads and the deepest top-of-book, and they are the reason trading has never looked cheaper or smoother. But their capital is uncommitted by definition. In stress, they withdraw — fast — and the depth that looked so reassuring evaporates exactly when it is needed. This is the cell where systemic liquidity risk concentrates: the flash crashes, the 2014 Treasury flash rally, the dash-for-cash of March 2020.

The structural shift over the last fifteen years has been toward the second kind of provider. Markets in calm conditions are deeper and cheaper than they have ever been precisely because uncommitted, fast, electronic capital dominates the order book. But that same shift means that the liquidity is more fragile in stress — more of it can simply leave. The machines did not make markets robust. They made calm-state liquidity abundant and stress-state liquidity flightier. Those are not the same thing, and macroprudential policy cares about the second one.

So what absorbed the last three shocks?

The tectonics underneath

If it was not the microstructure — if anything, the microstructure got more fragile — then the resilience has to have come from somewhere else. The honest answer is that it came from the slow, unglamorous accumulation of reforms layered on top of that fragile microstructure, compensating for it.

I want to resist the temptation to crown a single reform as the cause, because the evidence does not support it and the truth is almost certainly a composite. But the strongest candidates are visible. Central counterparties have been pushed toward less procyclical margin models, so that a price spike is less likely to trigger the kind of self-reinforcing margin call that drove hedgers out of gas in 2022. The gilt crisis prompted liquidity-buffer requirements for liability-driven investment funds, so that the specific doom loop of 2022 is harder to set off. And the Federal Reserve’s Standing Repo Facility — established in 2021 as a backstop for funding markets — has quietly matured into a more usable tool, with daily morning operations added in June 2025 and, by December 2025, its aggregate cap removed in favour of full allotment. It is telling that the facility was actually used — it lent over $10 billion in a single day at the end of June 2025, its largest draw since inception — quietly, without drama, which is rather the point. A backstop that works at the routine, technical level is one that may never need to be deployed at the dramatic level.

These are the shifting tectonic plates of the regulatory landscape, not a single silver bullet. And not all of the adjustment was regulatory: some of it was behavioural. The desks that lived through the margin spirals of 2022 and the funding scramble of 2020 now manage collateral and position-sizing differently, whether or not a rule required them to — institutional memory is itself a buffer, if a perishable one. But one prominent reform is conspicuously not yet among the formal causes: the SEC’s Treasury central-clearing mandate, which will require central clearing of cash Treasuries from the end of 2026 and repo from mid-2027, has not yet taken effect. Whatever resilience we have seen in 2024–2026, it cannot be credited to a rule that is still prospective. That matters, because it means the most significant structural reform to the largest market in the world is still ahead of us — and untested.

The test that hasn’t come

Here is where I have to be honest about the limits of the argument, because the temptation to over-read three quiet shocks is strong and the cost of giving in to it is high.

The three shocks that were absorbed without intervention — yen carry, Liberation Day, Iran/Hormuz — were all, fundamentally, the repricing shocks I flagged at the outset. Asset prices moved violently as the market digested new information about tariffs, rates, or geopolitical risk. They were not funding shocks. Nobody’s collateral became unfundable; no clearing member faced a margin call it could not meet; the repo market did not seize. The dysfunction of 2020 and the gilt spiral of 2022 were different in kind: they were crises of funding and collateral, where the problem was not the level of prices but the inability to finance positions at any price.

The reforms I have described are aimed precisely at funding and collateral fragility — at margin procyclicality, at liquidity buffers, at the availability of a funding backstop. But they have not yet been tested by the kind of shock they were designed to withstand. A repricing shock that the market takes in stride is encouraging. It is not proof that the next funding shock will be absorbed the way the last three repricing shocks were. The true test of the reinforced plumbing is a stress that hits the plumbing directly, and we have not had one since the reforms went in.

So the cleaner reading of the evidence is this. Markets did not become resilient because the machines learned to provide liquidity in a crisis — they did not, and the structural shift toward uncommitted liquidity provision means the order book is in some ways more fragile than before. Markets coped because a decade of dysfunction produced a slow accumulation of reforms that compensated for that fragility, and because the recent shocks happened to be of the type those reforms address. That is a real achievement, and the people who built those reforms deserve more credit than the algorithms are getting. But it is a conditional achievement, resting on a structure of buffers that has to hold, and on a particular kind of shock continuing to be the kind we get.

The market learned to bend. Whether it has learned not to break, we will only find out when something pushes on the part that bent last time.

Paweł Fiedor — The Macro Prudential View

The views expressed are the author’s own and do not necessarily reflect those of any institution with which the author is or has been affiliated.

Sources: SEC & CFTC, Findings Regarding the Market Events of May 6, 2010 — https://www.sec.gov/news/studies/2010/marketevents-report.pdf; Joint Staff Report, The U.S. Treasury Market on October 15, 2014 — https://home.treasury.gov/system/files/276/joint-staff-report-the-us-treasury-market-on-10-15-2014.pdf; Federal Reserve, FOMC statement of 23 March 2020 — https://www.federalreserve.gov/newsevents/pressreleases/monetary20200323a.htm; Office of Financial Research, The London Metal Exchange Nickel Market Crisis (WP 24-09) — https://www.financialresearch.gov/working-papers/files/OFRwp-24-09_central-clearing-and-trade-cancellation.pdf; Bank of England, gilt market operation announcement, 28 September 2022 — https://www.bankofengland.co.uk/news/2022/september/bank-of-england-announces-gilt-market-operation; Swiss National Bank, Credit Suisse liquidity assistance statement, 19 March 2023 — https://www.snb.ch/en/mmr/reference/pre_20230319/source/pre_20230319.en.pdf; Bank of Japan, Deputy Governor Uchida speech, 7 August 2024 — https://www.boj.or.jp/en/about/press/koen_2024/ko240807a1.htm; Federal Reserve, FOMC statement of 19 March 2025 (QT taper) — https://www.federalreserve.gov/newsevents/pressreleases/monetary20250319a.htm; Federal Reserve, FOMC statement of 29 October 2025 (end of runoff) — https://www.federalreserve.gov/newsevents/pressreleases/monetary20251029a.htm; Federal Reserve Bank of New York, Standing Repo Facility operating policy, 28 May 2025 and 10 December 2025 — https://www.newyorkfed.org/markets/opolicy/operating_policy_250528 and https://www.newyorkfed.org/markets/opolicy/operating_policy_251210; U.S. Securities and Exchange Commission, Treasury Clearing implementation — https://www.sec.gov/securities-topics/treasury-clearing; Bank of England, Financial Stability Report, July 2023 (LDI) — https://www.bankofengland.co.uk/financial-stability-report/2023/july-2023. Volatility data: CBOE (VIX), ICE BofA (MOVE), Qontigo/STOXX (VSTOXX). Gas price and open-interest data: ICE Endex (TTF) via Investing.com; ICE Global Natural Gas Futures (TTF, NBP, JKM, North American hubs). Fed balance-sheet data: Federal Reserve H.4.1 via FRED (TREAST). CUSIP breadth: Federal Reserve Bank of New York, Outright Purchases and Sales of Treasury Securities.

PIK is not an anomaly

Imagine a sponsor-backed mid-market borrower. The original 2022 senior secured term loan was clean: cash interest paid quarterly, fixed and floating spreads, standard maintenance covenants. By late 2024 the borrower’s cash flow has deteriorated. Rather than mark the loan, restructure it, or trigger a covenant breach, the lender and the sponsor agree to convert a portion of the interest from cash-pay to PIK — payment-in-kind, where the interest doesn’t actually leave the borrower as cash but accrues to the principal balance instead. The headline default rate is unaffected. The loan continues to be marked at or near par. The BDC holding the loan reports interest income, including the PIK component, in its quarterly results. The cash distribution to LPs goes out on schedule, funded partly by other loans and partly, increasingly, by new equity raises or draws on the fund’s credit lines.

No one has crystallised a loss. The borrower’s principal is growing. The reported numbers look stable, for now. Because valuations in private credit are GP-determined and infrequently tested against arms-length markets, the “for now” can persist much longer than common sense expects.

This is not a small phenomenon. Based on my own aggregation of the top fifteen exchange-traded BDCs’ EDGAR filings, PIK income has risen from roughly 4% of total interest income at end-2022 to about 6% by Q1 2026 on a four-quarter rolling basis. The more striking shift is where PIK now sits: at Ares Capital Corporation, the largest exchange-traded BDC and one of the most conservatively-run, the first-lien share of PIK-paying investments (measured by fair value) has risen from 60% in 2021 to 76% by year-end 2025. PIK was historically a feature of distressed mezzanine and second-lien paper. It now sits in senior secured paper at the most benchmark-quality BDC in the market.

The FSB’s Report on Vulnerabilities in Private Credit, published in May 2026 after a year-long investigation, made the data limitations explicit. The report states that private credit “remains untested in a prolonged economic downturn” and that authorities face “significant data challenges” in monitoring the bank-fund interconnection. It also flagged “the rising use of payment-in-kind arrangements” as one indicator of deteriorating credit conditions. After a year of work involving every major macroprudential authority in the developed world, the official sector is still working around structural data blind spots — unable to map, with anything approaching precision, how much PIK is outstanding, who holds it, or what these valuations would survive in a real downturn.

This is not a small market. The FSB estimates the global private credit asset class at $1.5–2 trillion, with direct bank credit lines to private credit funds running in the hundreds of billions. The interconnection is large enough that the data gaps matter.

I want to be careful about what kind of claim I am making here. PIK is not a fraud. It is not even, on any individual loan, a problem. PIK toggles have a legitimate role in financing structures where cash flows are lumpy or where a sponsor needs flexibility through a specific investment phase. What is interesting is not any single PIK toggle. What is interesting is the equilibrium — the fact that every participant in the capital structure has private incentives pointing the same way.

That equilibrium is the subject of this essay. Private credit’s PIK creep is the contemporary illustration, but the underlying pattern is much older. It is, I will argue, the central problem in financial stability — and the one that macroprudential policy, for reasons that have to do with how the toolkit was designed rather than with anyone’s incompetence, is least well-equipped to address.

Why the equilibrium holds

Walk the stack of incentives, one participant at a time.

The borrower wants survival. Cash interest converted to PIK is, for a stressed borrower, the difference between a default and a non-default. Even if the principal is compounding at 12% — and that is roughly where current PIK rates sit — the alternative is worse. The borrower is not making this trade strategically; it is making it under duress.

The sponsor’s interest aligns. Injecting fresh equity into a stressed portfolio company crystallises a down-round, recalibrates the fund’s mark on the position, and hits the sponsor’s IRR. A PIK arrangement protects all three. It is the sponsor’s own version of smoothing, and the GP-LP interests align on this — neither party benefits from a marked-down NAV at this stage of the fund’s life.

The General Partner of the credit fund holds the loan at fair value, which is its own determination, audited but not market-priced. As long as the loan continues to pay interest (whether in cash or in kind) and as long as no covenant trips, the GP can defend a near-par mark. The GP earns management fees on assets under management and performance fees on returns above a hurdle. Both are smoother if losses don’t crystallise. Beyond the direct fee economics, the GP is in a competitive market for institutional capital where marked-down NAVs become a fundraising problem within months. The incentive to extend rather than mark is structural.

The Limited Partner — pension fund, insurance company, sovereign wealth fund — receives a cash distribution on the fund’s reporting schedule, and the distribution does not distinguish between cash interest received from healthy borrowers and PIK income accrued from stressed ones. The LP’s allocators are evaluated on relative performance against a benchmark, and the benchmark is constructed from the same fund universe with the same valuation conventions. There is no LP that has a strong unilateral incentive to demand a fair-value crystallisation.

For the BDC structure specifically, the regulatory framework adds an additional twist. US Regulated Investment Company (RIC) tax status requires the BDC to distribute at least 90% of its taxable income annually to maintain that status. That taxable income includes PIK. The BDC therefore must pay cash dividends on income it did not receive in cash. The cash for those dividends comes from other loans, from credit-line draws, from new equity raises, and — as the PIK share grows — from increasingly complex funding manoeuvres to sustain the dividend policy. iCapital argues that there is natural pressure on BDCs to keep PIK income below roughly 10% of total interest income, because above that level cash-distribution stress becomes structural. Prospect Capital, one of the more PIK-heavy listed BDCs, operates at roughly one-third of net investment income based on its filings — well past the threshold.

The mechanical consequence deserves to be stated plainly. When a BDC raises new equity, draws on a subscription line, or rolls a credit facility to fund a cash distribution against PIK income, real cash is leaving the system. The fund is burning actual liquidity — investor capital, bank lending capacity, dividend reserves — to sustain the appearance of a smooth, non-defaulting portfolio. The equilibrium is not a free lunch. It is a slow drawdown of liquid resources to defer the recognition of a credit problem, financed by the rotation of new capital in to pay out old.

The bank — and there is usually a bank somewhere in the structure — earns commitment fees on the subscription line or NAV-backed facility extended to the fund (typically collateralised by fund NAV and short-dated), and avoids any direct credit exposure to the underlying borrower. The bank’s balance sheet looks safer than it would have if the bank had made the loan directly. The economic exposure is largely the same, but it sits in a structure that doesn’t show up on the bank’s lending book or in its regulatory disclosures.

The point of walking through the stack is that nothing in it is wrong on its own terms. Every participant is responding rationally to its own incentive structure. The contractual fix — converting a cash-flow problem into a balance-sheet item — works at the level of each individual contract. What fails is the aggregation. The system as a whole is taking on credit risk that is not visible to any single participant, including the prudential supervisor.

This is often called “extend and pretend,” and it is recognised, in retrospect, as a feature of essentially every credit cycle for at least four decades.

The same machine, different fuel

In my reading of the post-1980 history of financial regulation, one of the most consistent patterns is not crisis followed by reform. It is innovation followed by smoothing, where smoothing means the introduction of some contractual or structural innovation that converts a cash-flow or credit problem into something that doesn’t trigger immediate recognition. Every cycle generates a new technology for doing this.

US savings and loans in the 1980s used regulatory accounting principles — RAP, distinct from GAAP — to defer recognition of losses on residential mortgages whose market value had collapsed when interest rates spiked. The RAP allowed S&Ls to amortise losses over the remaining life of the loan rather than mark them at issuance. By the time the system was forced to recognise the underlying insolvency, the bill was several hundred billion dollars. In each case I describe in this section, the binding choice was not whether losses existed, but when — and in which set of accounts — they would be recognised.

Mortgage securitisation in the 1990s and 2000s separated the originator of a loan from the bearer of its credit risk. The originator earned a fee on issuance and passed the cash flows to investors via structured vehicles whose ratings depended on internal models that the rating agencies themselves did not fully understand. The CDO bid in 2005–2007 produced a market in which the demand for AAA-rated mortgage paper exceeded the underlying supply of AAA-quality mortgages, with the difference made up by financial engineering. The losses crystallised in 2008.

Leveraged loans and CLOs in the 2010s migrated the same originate-and-distribute model into the corporate credit space, with two refinements. First, covenant-lite documentation removed most of the maintenance triggers that historically forced workouts before losses became catastrophic. Second, the CLO buyer base — primarily insurance companies and bank trading desks searching for AAA-rated paper — provided structurally inelastic demand at the top of the capital structure. By the early 2020s, over 85–90% of new leveraged loans were covenant-lite, and the global CLO market had grown to around $1–1.4 trillion.

Private credit and PIK in the 2020s are, in my read, the next iteration — the same equilibrium I described earlier, refracted through different financial-engineering vocabulary. The contractual innovation is the PIK arrangement; the structural innovation is the move from public bond markets to private fund vehicles where valuations are GP-determined and disclosure is limited to LPs. Each generation looks technical and specific enough that the previous generation’s lessons “don’t apply.” Each generation is the same equilibrium — converting cash-flow stress into something that doesn’t have to be recognised today, because everyone in the stack is happier that way.

This is not the only path innovation can take. Plain-vanilla interest-rate swaps, simple pass-through securitisations, and CCP-cleared derivatives have all become standard infrastructure without obvious crisis episodes. The pattern I am identifying applies to the subset of innovation that combines leverage, opacity, and contractual smoothing of credit stress — which is, on the evidence of the last forty years, the consequential subset.

What is common across the consequential cases is not a failure of regulation in the narrow sense. Capital requirements existed in 1985, in 2005, in 2015, in 2025. They have generally gotten tighter over time, not looser. What is common is that the regulation operates on quantities — how much capital, how much liquidity, how concentrated the exposure — while the innovation operates on incentives — who recognises losses when, who captures the upside, who bears the downside if the bet doesn’t work. The architecture of post-2008 macroprudential policy was built to manage quantities. It works for that. It does not, by its own design, address the contractual and structural margins where the next equilibrium is being built.

This is the central argument of this essay. The rest is detail.

What macroprudential policy actually does

Before going further it is worth being precise about what the post-2008 macroprudential toolkit consists of, because the argument is not that macroprudential policy is bad — it is that the toolkit’s design defines its perimeter, and that perimeter is largely orthogonal to the incentive structures that drive the kind of equilibrium described above.

The bank-side toolkit, organised by category, has six main families. Capital tools — the Capital Conservation Buffer, the Countercyclical Capital Buffer, the Systemic Risk Buffer, the G-SII and O-SII buffers — together raise the equity-to-assets ratio of regulated banks above the Basel III minimum, in some jurisdictions substantially. Risk-weight constraints — output floors, IRB restrictions, sectoral risk-weight floors — limit the extent to which banks can use internal models to reduce the denominator of their capital ratio. The leverage ratio provides a non-risk-based backstop against the gaming of risk weights, and in Europe has been binding for a subset of large institutions since CRR2 took effect in 2018. Liquidity tools — the Liquidity Coverage Ratio and the Net Stable Funding Ratio — require banks to hold sufficient high-quality liquid assets to survive a 30-day stress scenario and to maintain a stable funding profile over a one-year horizon. Large exposure limits and concentration rules cap the credit risk a bank can take to a single counterparty or sector. Borrower-based measures — LTV, DTI, DSTI, maturity limits on mortgages — operate on the demand side of the lending market.

Beyond banks, the macroprudential perimeter has expanded into non-bank financial intermediation, with three main vectors. AIFMD Article 25 gives national authorities the power to impose leverage limits on alternative investment funds. EMIR margin and CCP resilience requirements address counterparty risk in derivatives markets. The MMF reform agenda restructured the prudential treatment of money market funds after the 2008 and 2020 runs.

Every item in this toolkit operates on a quantity: amount of capital, ratio of capital to assets, share of liquid assets in the balance sheet, size of exposure to a single counterparty, leverage of a fund vehicle. None of them operates directly on a contract — on how interest is structured, how covenants are written, how valuations are determined, how compensation is linked to outcomes. (Supervisors do issue expectations on underwriting standards through guidelines and SREP letters, but these are not primary macroprudential tools, and they operate at the institution level rather than at the market level.) Bail-in and MREL come closest to touching incentives, in that they were explicitly designed to reset bondholder expectations about loss-absorption capacity, and CRD V’s remuneration rules — deferral, malus, clawback — reach into compensation structure. But as we will see, the latter has been substantially arbitraged and the former applied unevenly. SREP capital add-ons under Pillar 2 give supervisors institution-specific discretion, but the discretion is exercised through the same quantity-based instruments as the rest of the toolkit.

There is a defensible objection at this point: that capital and MREL do reach incentives indirectly, through the cost-of-capital channel. Higher required capital makes risk-taking more expensive at the margin; higher MREL makes bail-in-eligible debt price the risk of loss; rising buffers compound through retained earnings into discount rates. This is true. But what the price channel adjusts is the price of risk-taking. It does not adjust the contractual terms through which risk is masked. A bank facing higher capital costs may demand a higher spread on a leveraged loan; it does not, through the price channel, get an instrument to constrain whether that loan can convert from cash-pay to PIK once made. The price channel changes the marginal economics of activities the framework can see. It does not bring activities the framework cannot see into the framework.

This is not a critique of the toolkit. The macroprudential framework was designed to address the failures most clearly diagnosed in the aftermath of 2008 — banks were undercapitalised, illiquid, and concentrated. The post-2008 reforms made banks better capitalised, more liquid, and less concentrated. The empirical literature on the effectiveness of macroprudential tools — Galati and Moessner’s BIS survey, the IMF’s iMaPP studies, the ECB’s Macroprudential Bulletin series — generally finds that the tools work for what they were designed to do.

The toolkit has also expanded. AIFMD Article 25 leverage limits, MMF structural reform, CRD V remuneration rules, and SSM Pillar 2 discretion all reach further than the framework did in 2010. Yet these expansions remain largely quantity-based, or — in the case of remuneration — have been substantially arbitraged, as the bonus-cap evidence later in this piece will show.

The argument is structural, not evaluative. The toolkit’s design constrains its reach. The kind of equilibrium described above — where PIK creep happens because every participant has private incentives pointing the same way — operates at margins the toolkit does not directly touch. The regulatory architecture has the tools to constrain how much bank capital sits behind a leveraged loan, but no comparable tools to constrain how that loan is contractually structured once made.

The deeper question, and the subject of the rest of this essay, is whether macroprudential authorities can — or should — develop tools that reach the contractual and incentive margins directly. The right place to start is where the post-2008 reform agenda itself started: the capital framework.

Capital alone hasn’t worked, but not for the reason most people think

After 2008, the regulatory response was dominated by capital. Basel III roughly tripled the minimum CET1 requirement; CRD IV and CRR layered the Capital Conservation Buffer, Countercyclical Capital Buffer, Systemic Risk Buffer, and G-SII/O-SII surcharges on top. The trajectory has been almost monotonically upward: average CET1 ratios for large international banks have risen from approximately 7% pre-crisis to comfortably above 14% by 2024. By any reasonable measure, large internationally-active banks are better capitalised today than at any point since the 1980s.

This was the right starting point. The 2008 crisis revealed that major banks were running with equity ratios of 2–3% of unweighted assets, supporting maturity transformation and credit creation that depended on continuous wholesale funding access. When that funding froze, the banks did not have the equity buffer to absorb mark-to-market losses while remaining solvent. The capital response is, in retrospect, the clearest success of the post-2008 reform agenda.

But it has limits. Two of them deserve attention.

The first limit is the one Haldane diagnosed in his 2012 “Dog and the Frisbee” speech. Regulatory complexity, beyond a certain point, becomes a tool of gaming rather than a constraint on it. The more granular the risk-weighting framework, the more parameters available for a sophisticated bank to optimise against. The internal ratings-based (IRB) approach was, in its design, supposed to align capital requirements more tightly with actual risk. In implementation, it produced significant divergence between banks holding similar portfolios — divergence that the EBA’s IRB benchmarking exercises have documented year after year. The output floor introduced under Basel IV is the multilateral response, but a partial one: it limits how far banks can use internal models to reduce risk weights, without addressing the underlying complexity that makes the gaming possible. Tarullo, in his April 2017 “Departing Thoughts,” made adjacent points from the regulatory side: the framework had become too complex for supervisors themselves to verify in real time.

The second limit is more fundamental and gets less attention. Capital regulation operates on the denominator of the loss-absorbing layer. Increase capital requirements, and equity holders bear more of any given loss. Useful — but it does not change who decides whether to take the loss-generating risk in the first place. That decision is made by management, on the basis of an incentive structure that allocates the upside of risk-taking to equity (via options, restricted shares, performance metrics that scale with ROE) and the downside to depositors, bondholders, and ultimately the sovereign. Capital regulation does not touch that asymmetry directly. It just changes the size of the buffer between management’s incentive and the taxpayer.

Admati and Hellwig pushed hard on the level of capital in The Bankers’ New Clothes (2024 edition) — arguing that bank capital should be substantially higher than current Basel standards, and that the conventional industry case against higher capital is built on flawed arguments about funding costs. Their analysis is rigorous, and the response from the official sector and from academic critics has, in my read, mostly conceded the basic point while disagreeing on the operational margin. Their argument is about level. The argument I make next — the Bebchuk-Spamann argument — is about structure.

The same logic, refracted, applies to private credit. The capital that sits behind a bank’s subscription line to a private credit fund is regulatory-light because the line is structurally senior, collateralised by fund NAV, and short-duration. That is a quantity argument that holds up under standard regulatory analysis. But the bank’s decision to extend the line, and the fund’s decision to use it for cash dividends to LPs rather than for borrower workout, is driven by incentive structures that no quantity tool reaches.

The incentive mechanism: a call option on bank assets

The cleanest formal statement of the bank-comp problem is Bebchuk and Spamann’s 2010 Georgetown Law Journal article, “Regulating Bankers’ Pay.” Their argument has a single moving part. A bank’s capital structure is overwhelmingly debt-financed: equity is typically 5–7% of assets, with deposits (50–60% of liabilities) and various forms of senior and subordinated debt filling the rest. Executive compensation is heavily linked to equity returns — through restricted stock, performance share units, ROE-based bonuses. The structure of the executive’s claim, then, looks like a long call option on the bank’s assets: substantial upside if asset values rise (equity is the residual claimant), capped downside at zero (because the executive does not personally fund losses below their own equity holdings, which are typically a fraction of one year’s compensation).

The mechanics are straightforward. With a thin equity layer at the top of a heavily-levered capital stack, small changes in asset values translate into large changes in equity value. A 1% increase in asset values, on a balance sheet where equity is 5% of assets, is a 20% increase in equity. Conversely, a 1% decline in asset values wipes out 20% of equity — but the executive’s exposure is asymmetric, because their pay is linked to equity returns when those returns are positive (vesting of options, performance bonuses paid in good years), while the executive does not personally absorb negative returns beyond their own holdings. The result is an executive payoff profile that is convex in asset volatility: the executive is, in option theory terms, long vega.

This is what the chart above shows. Compensation tracks equity at the top of the stack; losses cascade downward through layers that share none of the upside. The depositor at the bottom of the cap structure is the residual loss-absorber, with explicit protection via deposit insurance schemes funded by the rest of the banking system and, in extremis, the sovereign. The implicit taxpayer backstop at the very bottom is not a flourish. It is what makes the option valuable. Without an implicit floor, the executive’s claim would not be a call — it would be a position in a residual claim with genuinely unbounded downside, and the optionality that drives the compensation argument would disappear.

The empirical evidence is consistent with what theory predicts. Cheng, Hong, and Scheinkman, in their 2015 Journal of Finance paper, showed that US banks with higher residual pay (the unexplained portion of total executive compensation) were more likely to fail in 2008, controlling for size, leverage, and asset composition. Bebchuk, Cohen, and Spamann had earlier documented, in The Wages of Failure (Yale Journal on Regulation, 2010), that the senior executives of Bear Stearns and Lehman Brothers extracted some $2.4 billion in cash bonuses and equity sales between 2000 and 2008 — money that did not flow back to creditors or to the FDIC when the firms failed. The compensation system, in their phrasing, was structured so that executives “made money during the build-up of risk that crashed their firms.” Cerasi, Deininger, Gambacorta, and Oliviero (BIS Working Paper 630, 2017) found that across a large international panel, banks with more equity-linked CEO compensation had higher CDS spreads and higher Z-score volatility — consistent with the option-like payoff inducing more risk.

The structural question this poses for regulation is whether the asymmetry can be addressed by any policy tool other than direct intervention in compensation structure. The Bebchuk-Spamann answer is essentially no. Capital requirements reduce the option’s intrinsic value but do not eliminate the convexity. Bail-in shifts more loss-absorption onto debt holders but does not change executive incentives. Deferred compensation rules push the payoff out in time but do not address its option-like nature. The only structural fix is to change what executives are paid with — to give them claims that share in the downside, not just the upside.

The parallel to today’s PIK structures is not hard to draw. The GP of a private credit fund has a similar option-like payoff: 20% carried interest above a hurdle (the upside), management fees on AUM (a base layer that does not decline with NAV losses below a certain band), and limited personal capital at risk in the fund. The compensation asymmetry is structurally identical to the bank-executive case Bebchuk and Spamann formalised. Only the capital-structure terminology differs.

What the EU has actually tried

The European post-crisis architecture has gone further than the US on incentives. This is not a partisan claim — it is the empirical record of legislation and implementation.

The BRRD (Bank Recovery and Resolution Directive, 2014) and SRMR (Single Resolution Mechanism Regulation, 2014) established a framework that placed loss-absorption onto a hierarchy of bondholders before any taxpayer support could be deployed. Article 18 of the SRMR specifies the three tests that must be met for SRB-led resolution: (a) the bank is failing or likely to fail; (b) no private or supervisory alternative exists; and (c) resolution is in the public interest. The framework was designed to make TBTF support politically and operationally costly enough that managers and creditors would price the bail-in risk into their decisions.

MREL (Minimum Requirement for Own Funds and Eligible Liabilities) operationalised the framework: each significant bank must hold a portfolio of bail-in-eligible debt sufficient to cover potential losses and a recapitalisation amount. The SRB’s MREL Dashboard reports that the banks under its mandate had built up MREL stocks averaging close to 28% of risk-weighted assets by end-2024 (SRB MREL Dashboard, end-2024) — well above pre-crisis subordinated debt levels.

CRD IV’s remuneration framework went further. From 2014, variable pay for identified staff was capped at 100% of fixed pay, extendable to 200% with shareholder vote. Deferral periods of 4–5 years became mandatory, with malus and clawback provisions for risk-management failures discovered after vesting. EBA Guidelines (EBA/GL/2021/04) provide the implementation detail. The CRD V update (2019) tightened the regime further on smaller and mid-sized institutions, addressing earlier proportionality exemptions.

ECB-led supervision via the SSM, established in 2014, provided centralised micro-prudential oversight of significant institutions, with SREP capital add-ons (Pillar 2 Requirement and Pillar 2 Guidance) giving the supervisor institution-specific discretion to layer capital requirements on top of Pillar 1.

This is, on paper, a more ambitious regulatory architecture than the US framework. Dodd-Frank’s bail-in framework (Orderly Liquidation Authority) has never been invoked since enactment in 2010, and is subject to 2018 Treasury guidance that narrowed the practical path to OLA, emphasising bankruptcy as the preferred route. The US compensation rules under Dodd-Frank Section 956, which would have imposed deferral and clawback requirements on incentive compensation at large banks, were proposed in 2011 and again in 2016 and have still not been finalised and implemented, despite being re-proposed in 2024. The Volcker Rule, while implemented, was substantially weakened in the 2020 amendments that loosened its application to proprietary trading and merchant banking.

What Europe attempted, the US did not try — or tried and abandoned. This is worth saying directly, because it sets up the question the next section takes on: where the European architecture has been tested in real cases, what did the results actually show?

Two natural experiments: bail-in and the bonus cap

Two events in 2017 provide the cleanest natural experiment we have on bail-in. Both involved failing banks meeting Article 18(1)(a) and (b) of the SRMR — failing or likely to fail, with no private alternative. Both required the SRB to decide whether to invoke resolution under (1)(c)’s public interest test. The two outcomes diverged completely.

Banco Popular was declared failing or likely to fail by the ECB on 6 June 2017, after a deposit run and an ELA collateral shortfall that left the bank unable to reopen on 7 June. The SRB triggered resolution within hours, applied the bail-in framework, and sold the bank to Santander for €1 on the morning of 7 June. The cap structure was applied as designed: shareholders 100% wiped, AT1 written down to zero, Tier 2 converted to equity which was then sold to Santander for €1, depositors preserved. Direct taxpayer cost: €0.

Veneto Banca and Banca Popolare di Vicenza were declared failing or likely to fail by the ECB on 23 June 2017, with the SRB issuing a same-day determination that resolution was not in the public interest under Article 18(1)(c). The reasoning given was that the banks’ functions were “not critical,” interconnectedness was “low,” and Italian insolvency proceedings would achieve resolution objectives to the same extent. The banks were placed into national liquidation. The European Commission approved Italian state aid for the resolution under Commission Decision SA.45664 within 48 hours.

The state aid package was substantial. The Commission decision authorised cash contributions to Intesa Sanpaolo of €4.785 billion (€3.5bn cash, €1.285bn restructuring lump sum), plus state guarantees of up to ~€12 billion on the funding gap and NPL transfer. Subsequent retail-bondholder compensation through the Fondo Indennizzo Risparmiatori, established by Italian Budget Law 145/2018, added another €1.575 billion over 2019–2021.

The reading I take from these two events — and others may read them differently — is that the bail-in framework works when it works, and the question is when it works. The Article 18(1)(c) public-interest test is the discretionary margin. In the Italian case, the public-interest test was applied in a way that allowed a national-law liquidation with state aid, effectively bypassing the SRB’s bail-in regime and shifting losses back to the sovereign balance sheet. The framework is the same in both cases; the application diverged on a single discretionary judgment.

This matters for incentives because what bondholders price is expected loss-absorption, not legal loss-absorption. If the expectation is that medium-sized banks in politically-sensitive jurisdictions can secure exemptions, the disciplining effect of the framework on bondholder behaviour is correspondingly diluted. This is not a critique of the framework or of the people applying it. It is an observation that the framework is structured to permit discretion at exactly the point where the structural-reform alternatives — which we will come to shortly — are structured to remove it. The CMDI (Crisis Management and Deposit Insurance) proposal of April 2023 is, in effect, an admission that the framework as it stands does not systematically work for mid-sized banks, and an attempt to plug the gap by expanding DGS use and resolution scope.

The bonus cap provides a different kind of natural experiment. EBA’s annual benchmarking of high-earner remuneration in EU banks reports the data needed for a clean comparison: 2013 (the last year before the cap, since CRD IV took effect for performance year 2014) and 2014 (the first year of binding cap).

The headline numbers are unambiguous. The average total compensation of EU high earners (≥ €1 million total compensation) was essentially unchanged: €1.89m in 2013, €1.91m in 2014. The composition flipped: average fixed pay rose from €454k to €840k (+85%), while average variable pay fell from €1.44m to €1.07m (−26%). The variable/fixed ratio collapsed from 317% to 127% — exactly as the cap mechanically required. The sample of EU high earners grew from 3,178 to 3,865 over the period as reporting harmonised, so the per-individual averages are the right metric for isolating the composition effect from sample growth.

Colonnello, Koetter and Wagner formalised the empirical pattern in their 2023 Journal of Accounting and Economics paper, using difference-in-differences identification on a larger panel of European banks. They documented what the literature calls the indemnification effect: banks responded to the variable-pay constraint by raising base salaries to maintain total compensation, with the level of total pay roughly preserved across the cap transition.

The economic interpretation matters. The cap was designed on the theory that variable pay drives risk-taking, and reducing variable pay relative to fixed pay should reduce risk incentives. The mechanical response of banks was to raise base salaries to maintain total compensation. This is exactly what the Bebchuk-Spamann framework would predict: if executive talent is competitively priced in a labour market, a constraint on one component of compensation will be offset by adjustments in others.

There is a second, less-discussed consequence worth flagging. By converting variable pay (which is cuttable in stress) into fixed pay (which is structurally rigid), the cap raised the operating leverage of EU banks’ compensation cost base. In a systemic downturn, variable pay can be reduced quickly to preserve capital; fixed salaries cannot. The cap, on this reading, did not just fail to discipline risk-taking — it made bank cost structures less flexible in exactly the scenario the regulator most cares about.

The UK provides the other end of the experiment. In October 2023, the PRA and FCA jointly removed the bonus cap entirely (PS9/23), citing exactly the arbitrage argument: the cap had pushed compensation toward fixed pay without reducing total compensation, and fixed pay is less responsive to performance — meaning the cap may have actually weakened the link between pay and risk discipline. Whether the UK was right to abandon the rule, or whether the abandonment trades one set of incentives for another, is a separate question worth its own essay. But the trajectory is striking: the UK first implemented the rule (as part of CRD IV transposition), saw a decade of evidence that the implementation did not achieve its goals, and abandoned it.

The same indemnification logic appears in today’s PIK structures, refracted into different vocabulary. The cap on cash distributions imposed by the RIC tax framework pushed BDCs to maintain headline distribution rates while their underlying cash receipts deteriorated. The constraint on one margin produced an adjustment on another: PIK accruals expanded, the dividend was funded by other means, and the headline numbers held. The system finds the path of least resistance — not because anyone is corrupt, but because every participant has private incentives pointing toward that path. The bonus cap and PIK are two manifestations of the same dynamic: rules that operate on one margin while the binding incentive operates on another.

Both cases illustrate the deeper pattern the rest of this essay develops. When regulation constrains one margin of the incentive structure, markets adjust on another — often in ways the original rule never anticipated. The question is whether the macroprudential framework can be designed to anticipate the adjustment, and whether the political-economy conditions exist to do so.

Goodhart’s boundary problem

The classical statement is Goodhart’s law: “Any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes.” Goodhart published this in the context of monetary aggregates in the 1970s, but the form is general. Any quantity that becomes a regulatory target ceases to be a reliable indicator of the underlying phenomenon, because the regulated population reorganises its activities to optimise against the target.

The macroprudential framework runs into a specific version of this problem. The framework is built on a regulatory perimeter — entities classified as banks, alternative investment funds, money-market funds, central counterparties — and within each perimeter operates with quantity-based instruments. The problem is that financial activity does not stay inside the perimeter when the regulatory cost of being inside it rises. The activity migrates outward, to non-bank vehicles, to off-balance-sheet arrangements, to jurisdictions and contractual structures where the regulator has less reach.

The empirical record on this is striking. iMaPP data — the IMF’s database of macroprudential actions covering 2010–2024 — show that European jurisdictions cumulatively implemented around 21 tightening actions per country on average, with the United States implementing around 13. Across the same period, the global private credit asset class grew roughly twelvefold, from $91 billion outstanding in 2010 to $1.246 trillion by 2024 (BIS data). The growth was not uniform — much of it concentrated in the latter half of the period — but the trajectory is unmistakable.

The pattern is not coincidence. As the quantity tools tightened on regulated balance sheets, the same credit risk migrated to the least-regulated edge — exactly as Goodhart’s boundary would predict. I want to be careful about what this correlation does and does not show. The chart does not establish that macroprudential tightening caused the migration to private credit. The growth of private credit is over-determined: yield-seeking institutional investors after a decade of low rates, the post-2008 retreat of banks from leveraged lending, the rise of private equity as the dominant ownership form in mid-market US business, regulatory arbitrage at the bank-fund interface. All of these mattered. The point is that the macroprudential framework was tightening throughout the period and did not, by its design, constrain the migration.

This is Goodhart’s boundary problem in the macroprudential context. The framework can tighten capital, tighten liquidity, tighten leverage limits for banks and for AIFs within its perimeter. It cannot, by direct instrument, prevent activity from migrating to entity types and contractual structures outside the perimeter. Each tightening creates marginal pressure for migration; the cumulative effect, over fifteen years, is a substantial transfer of credit-creation activity to vehicles where the prudential supervisor has less visibility.

The natural response — and the one that has been pursued throughout the period — is to expand the perimeter. AIFMD II in 2024 extended leverage limits and reporting requirements to a broader population of alternative funds. The FSB’s NBFI work programme since 2022 has tried to identify systemic activities across non-bank intermediaries and bring them within prudential reach. The ECB’s Macroprudential Strategy 2024 review specifically called out NBFI as a strategic priority.

Each expansion buys some visibility. But the expansion has a logical limit: every entity type the regulator brings inside the perimeter incentivises the next iteration of innovation outside it. The PIK arrangement in a BDC subscription line is a contemporary illustration. AIFMD II expanded the perimeter; the contractual structure that combines BDC distribution policy with sponsor IRR protection with GP carry economics sits at the contractual margin that no expansion of the entity perimeter directly reaches.

The deeper question is whether expanding the perimeter is the right response, or whether the regulatory architecture needs a different theory of where to act — one that operates on contract design rather than entity type. The next section takes on the three approaches that have been proposed and the frictions each runs into.

Three approaches, three frictions

If the macroprudential toolkit, as currently designed, cannot directly reach the incentive structures that drive the kind of equilibrium described earlier, what are the alternatives? There are essentially three, and each runs into a different binding constraint.

The first approach is structural reform: removing the activities or organisational forms that generate the problematic incentives in the first place. The intellectual genealogy runs through Glass-Steagall, Vickers (the UK’s Independent Commission on Banking, 2011), Liikanen (the EU’s High-Level Expert Group, 2012), and the Volcker Rule (the US’s 2010 Dodd-Frank provision). The proposals differed in detail but shared a common logic: ring-fence retail banking from investment banking, or prohibit certain trading activities entirely, or break up entities deemed too complex to supervise. By altering the structure rather than the parameters, structural reform aims to remove the underlying option-like payoff that drives the Bebchuk-Spamann mechanism.

The friction is political economy. The benefits of structural reform are dispersed (general financial stability, fewer crises) while the costs are concentrated on specific institutions and their employees. Mancur Olson’s collective-action logic predicts exactly which side wins in this configuration. The UK’s ICB recommendations were implemented but in diluted form: the ring-fence applies only to the very largest banks and the operational separation has been progressively softened. Liikanen was formally withdrawn by the European Commission in 2017. Volcker survived but was substantially weakened in 2020. The structural-reform path has not failed for intellectual reasons. It has failed for political-economy reasons that were predictable in advance.

The second approach is direct incentive regulation: rules that target compensation structure, contract design, or specific forms of risk-taking directly. CRD IV’s bonus cap is the cleanest example. The UK PRA’s Senior Managers Regime, which makes senior managers personally accountable for prudential failures, is another. EBA’s remuneration guidelines, which constrain deferral periods, malus, and clawback, fall in this category. So do underwriting standards expressed in supervisory letters, which try to constrain how loans can be structured.

The friction is arbitrage. Pay structures adapt around the rule. The bonus cap pushed compensation toward fixed pay without reducing total compensation. The Senior Managers Regime has changed reporting lines without obviously changing behaviour. Underwriting guidelines on covenant-lite loans were largely ignored because they were not formally binding. Where rules are binding, the regulated population adapts; where they are not binding, the rules do not have force. The UK’s decision to abandon the bonus cap in October 2023 is the most direct admission of this dynamic.

The third approach is perimeter expansion: bringing new entities and activities under the prudential framework as they emerge. AIFMD, MMF reform, the FSB’s NBFI agenda, ESRB activity-based recommendations all sit here. The logic is to chase the activity wherever it goes, rather than to constrain what activity can do.

The friction is Goodhart’s boundary problem — the issue covered in the previous section. Each tightening creates marginal pressure for migration outward. The perimeter expands; the next iteration of innovation appears at the new margin. The expansion is necessary — without it, activity migrates faster than the framework adapts — but it is not sufficient, because the dynamic does not converge to an equilibrium where the framework catches all systemic activity.

Each of these approaches has had its serious advocates. Each is genuinely useful at the margin. None has been able to address the core problem at scale, because each runs into a different binding constraint. The structural-reform proposals are diluted by political economy. The direct-incentive rules are arbitraged. The perimeter expansion is chased by Goodhart’s logic.

(A separate debate, which I am consciously not engaging with here, concerns whether the European architecture can be made more credible by completing Banking Union — common deposit insurance, full single rulebook, removal of national exemptions on resolution. That conversation is important, but it is about credibility within the existing framework, not about the framework’s reach. This essay is about the latter.)

What this leaves is a macroprudential framework that has done what it was designed to do — capitalised banks, made them more liquid, made them less concentrated — but that has not addressed and probably cannot address the kind of equilibrium I described at the beginning. The PIK creep, on this reading, is not the result of regulatory failure in the conventional sense. It is the natural expression of a framework that operates on quantities while the binding incentives operate on contracts.

What might move the needle

Against this backdrop of institutional frictions, what, if anything, can macroprudential authorities do to move the equilibrium? I am going to be modest about claims here. I do not think there is a single instrument that resolves the problem this essay has been describing. What I do think is that the framing of the policy debate has, over fifteen years, settled into asking the wrong questions — and that reframing the questions is, in itself, useful.

Three angles deserve more attention than they have received.

The first is transparency and data infrastructure. The FSB’s May 2026 report on private credit is candid about the data gaps. The most actionable response is not to wait for harmonised disclosure regimes, which are slow to negotiate and easy to dilute. It is to make existing reporting infrastructure work harder. AIFMD reporting templates could be extended to require loan-level disclosure on PIK accruals, covenant amendments, and valuation methodologies. Bank reporting on subscription lines and NAV-backed facilities could be made granular enough that supervisors can see the underlying exposure rather than just the credit-line commitment. The MMF reform agenda showed that targeted disclosure requirements, well-designed, can have substantial effects on behaviour. The same logic should apply to private credit.

The second is the contractual margin. The cleanest insight from the bank-comp literature — that compensation should track the cap structure as a whole rather than just equity — is implementable. The “inside debt” literature, including Edmans and Liu (2011, Review of Finance) and the operationalisations proposed in Bebchuk-Spamann themselves, argues for compensating bank executives partly in subordinated debt or other loss-absorbing instruments (extensions of the deferral and malus logic already in CRD V, rather than departures from it). Various deferred-pay vehicles linked to bank-wide loss-absorption performance, rather than equity returns, are another path to the same end. The structural problem with the current framework is that it constrains the level of variable pay without constraining its composition. Constraining composition — requiring a portion to be linked to subordinated claims or loss-absorbing instruments — addresses the option-like payoff directly. For private credit, the analogue is GP carry structures that share in NAV declines as well as gains. Whether this is achievable through fund-prospectus disclosure requirements or through LP fiduciary standards is a separate question, but the structural fix is identifiable.

The third is credibility on the resolution framework. The Banco Popular/Veneto comparison is not an argument for abolishing the public-interest test. It is an argument for narrowing the discretion that the test permits, or for separating the politically-sensitive judgment from the technical resolution decision. The CMDI proposal moves in this direction by expanding the scope of resolution and clarifying the DGS-funded path for mid-sized banks. Whether the final version of CMDI, when negotiated, will narrow the discretion enough to change bondholder behaviour is an open question. But the direction of travel — narrowing rather than expanding the room for case-by-case judgment — is the right one if the framework is to have ex-ante disciplining effect.

I am not putting these forward as a programme. I am putting them forward as the angles that follow from the analysis. Each of them runs into one or more of the frictions described above. Transparency proposals face the same political-economy resistance that structural reform faces, but at lower intensity. Contractual-margin reforms face industry pushback comparable to compensation regulation in general, but with the advantage that the literature supporting them is robust. Resolution-framework credibility faces sovereign-political resistance, but the CMDI process suggests there is at least appetite for incremental progress.

What none of these does is dispose of the underlying problem. The configuration I described in the PIK case is, in my reading, a permanent feature of financial systems with private capital allocation, competitive funding markets, and a generalised expectation of public support in extremis. The point is not to dissolve it. The point is to slow its growth and to make its manifestations more visible to supervisors before they crystallise.

What we have established

This essay has tried to make a single argument with several supporting claims.

The argument is that macroprudential policy, as currently designed, operates on quantities — capital, liquidity, leverage, exposure — while the equilibria that drive financial fragility operate on incentives. The post-2008 reform agenda has made banks better capitalised, more liquid, and less concentrated, and that is a real and substantial achievement. But it has not addressed the contractual and structural margins where the next equilibrium is being built, and the design of the toolkit does not permit it to do so directly.

The supporting claims are five.

First, the PIK creep in private credit is not an isolated phenomenon. It is the contemporary expression of a pattern that runs back through cov-lite leveraged loans, through mortgage securitisation, through the S&L crisis: contractual or structural innovation that converts cash-flow stress into balance-sheet items that do not require immediate recognition.

Second, the equilibrium holds because every participant in the capital structure has private incentives pointing the same way. This is not corruption or incompetence. It is the natural product of the contractual and fiduciary structures within which the participants operate.

Third, the post-2008 capital framework, while a genuine success at what it was designed to do, has not addressed the structural asymmetry that Bebchuk and Spamann identified — the option-like payoff that bank executives hold on a thinly-capitalised cap structure. Capital regulation changes the size of the buffer between management’s incentive and the taxpayer, but does not change the asymmetry itself.

Fourth, the European post-crisis architecture has gone further than the US on incentive-side regulation, and the natural experiments — Banco Popular versus Veneto, the bonus-cap implementation between 2013 and 2014 — are genuinely informative about what direct incentive regulation can and cannot do. The bail-in framework works when the political conditions for invoking it exist; the bonus cap was arbitraged through fixed-pay adjustments that left total compensation roughly unchanged.

Fifth, each of the three approaches to addressing incentives directly — structural reform, direct incentive regulation, perimeter expansion — runs into a different binding constraint. Structural reform is diluted by political economy. Direct incentive regulation is arbitraged. Perimeter expansion is chased by Goodhart’s boundary problem. None of these is a fatal objection; all of them are reasons why progress has been incremental.

The macroprudential scorecard in the chart above is the synthesis of this argument. Most cells in the matrix are grey — pairings of policy tools with incentive types where the tool does not, by its design, reach the incentive. The dominance of grey is the visual restatement of the argument: most policy tools do not apply to most incentive structures. The handful of green cells indicate genuine matches, mostly in the leverage-ratio backstop against model gaming and the liquidity-tool response to retail wrapper mismatches. The yellow cells are partial matches, often through AIFMD’s reach into fund-side activities. The red cells — risk-weight insensitivity to compensation convexity, the role-based-allowances arbitrage of the bonus cap, selective application of the public-interest test, the documentation opacity of PIK and covenant-lite — are the explicit cases of arbitrage where the rule was tried and the market adjusted around it.

Which brings us back to where we started. PIK in first-lien private credit is the latest expression of this incentive pattern. It is not a fraud, it is not a bubble, and it is not the product of regulatory failure in the narrow sense. It is the natural equilibrium of a system in which every participant — borrower, sponsor, GP, LP, BDC, bank — has private incentives pointing the same way, and in which the macroprudential framework, as currently designed, cannot reach the contractual margin where the equilibrium forms. Whether the next downturn crystallises the underlying credit problem in private credit, in some adjacent corner of the financial system, or — most likely — in a form that nobody is currently watching, the structural argument is the same. The fault line is at the contractual margin. The toolkit operates on the balance sheet.

That is the wrong margin. And the structural reason it is the wrong margin is not that the macroprudential framework has failed. It is that the framework was never designed to act there in the first place.

Paweł Fiedor - The Macro Prudential View

Views expressed are personal and do not represent the institutions with which the author is affiliated.

Sources and references

Chart 1 (PIK creep timeline) compiled from author’s aggregation of SEC EDGAR 10-K and 10-Q filings for the top fifteen exchange-traded BDCs, four-quarter rolling basis. Ares Capital Corporation first-lien PIK share computed from ARCC Schedule of Investments (measured by fair value). Chart 5 (bail-in case comparison) drawn from SRB Decision SRB/EES/2017/08 on Banco Popular Español S.A. (7 June 2017); SRB Decision SRB/EES/2017/11 and SRB/EES/2017/12 on Veneto Banca S.p.A. and Banca Popolare di Vicenza S.p.A. (23 June 2017); European Commission State Aid Decision SA.45664 (25 June 2017); and Italian Budget Law 145/2018 establishing the Fondo Indennizzo Risparmiatori. Chart 6 (bonus cap natural experiment) computed from EBA Report on Benchmarking of Remuneration Practices and Data on High Earners 2013 (Annex I) and EBA-Op-2016-05, Report on Benchmarking of Remuneration Practices at EU Level and Data on High Earners (data as of end-2014) (Annex I), averages per individual. Chart 7 (private credit growth vs macroprudential tightening) uses private credit outstandings from Avalos, Doerr and Pinter, The global drivers of private credit (BIS Quarterly Review, March 2025) and cumulative macroprudential actions from the IMF integrated Macroprudential Policy (iMaPP) Database.

Cited reports and primary documents: FSB, Vulnerabilities Associated with Private Credit (May 2026); iCapital, Painting a PIKture: The Benefits and Risks of PIK in Private Credit (2025); SRB, Minimum Requirement for Own Funds and Eligible Liabilities (MREL) Dashboard, Q4 2024; European Commission, Proposal for a Regulation amending the BRRD and SRMR — Crisis Management and Deposit Insurance framework (18 April 2023); PRA, PS9/23: Remuneration: Ratio between fixed and variable components of total remuneration (’bonus cap’) (October 2023); ECB Banking Supervision, ECB Macroprudential Bulletin (various issues).

Cited academic literature: Admati and Hellwig, The Bankers’ New Clothes: What’s Wrong with Banking and What to Do about It (Princeton University Press, expanded 2024 edition); Bebchuk and Spamann, “Regulating Bankers’ Pay”, Georgetown Law Journal 98 (2010); Bebchuk, Cohen and Spamann, “The Wages of Failure: Executive Compensation at Bear Stearns and Lehman 2000-2008”, Yale Journal on Regulation 27 (2010); Cerasi, Deininger, Gambacorta and Oliviero, “How post-crisis regulation has affected bank CEO compensation” (BIS Working Paper 630, 2017); Cheng, Hong and Scheinkman, “Yesterday’s Heroes: Compensation and Risk at Financial Firms”, Journal of Finance 70 (2015); Colonnello, Koetter and Wagner, “Compensation regulation in banking: Executive director behavior and bank performance after the EU bonus cap”, Journal of Accounting and Economics 76 (2023); Edmans and Liu, “Inside Debt”, Review of Finance 15 (2011); Galati and Moessner, “Macroprudential Policy — A Literature Review” (BIS Working Paper 337, 2011); Goodhart, “Problems of Monetary Management: The U.K. Experience”, Papers in Monetary Economics (Reserve Bank of Australia, 1975); Haldane, “The Dog and the Frisbee” (speech at the Federal Reserve Bank of Kansas City Jackson Hole Symposium, August 2012); Tarullo, “Departing Thoughts” (speech at the Woodrow Wilson School, Princeton University, 4 April 2017).

The Financial Stability Board’s first dedicated report on private credit, published 6 May, lands at a moment when European regulators are visibly turning their attention to the asset class. Frank Elderson, vice chair of the ECB’s supervisory board, said in an interview reported by Barron’s that European private credit “bears watching.” Earlier this month, the Eurosystem published its own roadmap for strengthening the macroprudential framework around non-bank financial intermediation — and private credit features prominently.

What stands out about the FSB report, though, is that the most interesting thing in it isn’t private credit. It is the structural picture of bank–nonbank interconnection that emerges, almost by accident, from the report’s data-availability annex. Read carefully, the report is best understood not as an asset-class warning but as a diagnostic of broader NBFI supervision. Banks and NBFIs increasingly operate as what the European NGO Finance Watch has called “communicating vessels,” and supervisors only partially see the connections between them. Private credit matters not because it is unique, but because it makes that wider problem legible. The same circles of risk — leverage layering, fund-bank financing loops, synthetic risk transfer, cross-border intermediation, opaque valuation — appear across the NBFI ecosystem. They are easier to see in private credit right now because it has grown fast enough to attract dedicated supervisory attention. The Eurosystem’s May paper makes the same point in regulatory language: data gaps in private credit are part of a wider NBFI data strategy still being built.

It is worth saying at the outset what the FSB also says: direct bank lending to private credit funds, where it can be separately identified, is below 0.5% of total bank assets in the FSB member data; private credit can support economic activity, diversify lending across the system, and provide tailored financing to underserved borrowers. The argument here is not that direct exposures are obviously systemic. It is that, even where direct exposures look manageable, the intermediation web and the data gaps are the supervisory issue the report points to.

The rest of this piece reads the FSB report through that lens, drawing also on the ECB Financial Stability Review, the EBA Risk Assessment Report, the OFR’s recent brief on counterparty exposures, and the Eurosystem’s May paper. Five charts walk through the architecture, the supervisory range of uncertainty, the cross-border asymmetry that defines European private credit, the SRT loop that closes some of the circles, and finally the data-availability heatmap that explains why all of this remains poorly observed.

The architecture

Start with the structural picture. The FSB’s ecosystem diagram shows banks financing private credit funds through multiple facilities — subscription lines, NAV facilities, fund portfolio financing — while those same funds lend onward to corporate borrowers. The vertical axis of the schematic above replicates that: euro area banks lend to EA-managed private credit vehicles, which lend on to borrowers either inside or outside the area. The horizontal axis is the harder part. Three further flows complicate the picture, and the FSB names each of them.

First, the destination of euro-area fund portfolio finance is not euro-area corporates. About 70% of EA fund portfolio finance is directed to non-EU borrowers, the FSB reports — most of them US-linked. The euro area’s private credit fund infrastructure is, in significant part, intermediating credit to firms outside the bloc.

Second, euro-area corporates’ own private credit borrowing largely doesn’t come from euro-area lenders. The ECB’s May 2024 Financial Stability Review found that only around a fifth of private credit borrowed by EA companies is provided by EA-managed funds. The other four-fifths comes from outside the area — predominantly US managers operating cross-border.

Third — and this is where the FSB’s analysis gets most interesting — banks may remain indirectly exposed to credit risk they thought they had transferred. Through synthetic risk transfers (SRTs), banks transfer the credit risk of their loan books to investors while keeping the underlying loans on their balance sheets. The EBA reports that private credit funds are the largest single investor group in EU bank SRTs. And, as the FSB itself acknowledges, it remains unclear how far banks fund the very NBFIs that buy their SRT risk. When that loop closes, the economic risk may remain partly within the bank–NBFI perimeter even as the regulatory capital requirement against the underlying loans has been reduced.

The FSB calls these “circles of risks.” The phrase is appropriate. It is also a structural description that applies well beyond private credit.

What we don’t know about size

Here is the most uncomfortable finding in the FSB report, and the one most easily missed. The report’s headline estimate of bank lending to private credit funds — about $220bn drawn and undrawn — is based on regulatory data from FSB member jurisdictions. But the report also references commercial and academic estimates that range up to $546bn for what is broadly a related perimeter.

The chart above shows where the four most-cited serious estimates land. The FSB member figure ($220bn, end-2024, five jurisdictions) is the lowest. The HKMA’s reconstruction from commercial data ($268bn, global, end-2023) sits modestly higher. Moody’s analysis of US bank filings ($300bn, drawn only, late 2025) is higher still. The FSB’s own summary of private-sector composite estimates puts the upper bound at $546bn — combining $300bn drawn loans, $155bn undrawn commitments, and $91bn from EU branches operating in the US, drawn from a body of research including Berg and Lee’s recent OFR brief (which itself, more narrowly, finds $74bn utilised and $123bn committed in US Y-14 data for participating banks).

The honest reading is not that supervisors see less than half of true exposure. It is that the available estimates measure different things — different geographies, different dates, drawn versus undrawn commitments, different scopes of what counts as “private credit” — and there is no harmonised perimeter to compare against. The spread is therefore not estimation error around a single number. It is a measurement of how much methodological choice drives the headline figure.

This is the data deficit story in one chart. It is also a leading indicator of the wider NBFI surveillance problem that the Eurosystem’s May paper is explicitly trying to fix.

A cross-border story Europe is not at the centre of

Of the three FSB findings sketched above, the one that should preoccupy European policymakers most is the cross-border asymmetry. The chart above puts it in a single panel.

Euro area-managed private credit funds direct roughly 70% of their portfolio finance outside the EU, predominantly to US-linked borrowers — the top bar. Euro area corporates, meanwhile, get roughly 80% of their private credit from non-EA lenders — the bottom bar. The two figures come from different but complementary datasets, and they tell the same story from opposite ends.

Read together, they suggest that the euro area sits in the middle of a cross-border intermediation chain rather than being the destination of either flow. EA fund infrastructure is helping place credit risk on mostly US-located corporate balance sheets. EA corporates are mostly funded by non-EA private credit funds. The euro area, in private credit, is a transit node — not a self-contained system.

What does this mean for supervision? At a minimum, it complicates the EA’s regulatory perimeter. The corporate credit risks that matter most for the euro area economy are largely originated outside it. The fund-level vulnerabilities most easily observed by EU supervisors — concentration, liquidity mismatch, leverage layering — increasingly relate to non-EA exposures. Effective monitoring requires looking at things the EA framework was not originally built to see.

This is not a uniquely private-credit problem. The same cross-border intermediation pattern appears in repo, derivatives, and prime brokerage. But private credit is the segment where the asymmetry is most clearly documented in recent regulatory work.

The SRT loop is closing

Now to the loop that gives private credit its specifically circular structure.

Synthetic risk transfers — instruments that move the credit risk of a bank loan book to outside investors while leaving the loans on the bank’s balance sheet — have grown rapidly. The right-hand panel above shows currently-outstanding protected loan pools by origination vintage, rising from around €30bn per year in 2017–2020 to €82bn in 2021, €113bn in 2022, and €143bn in 2023. The 2024 H1 partial-year figure of €63bn suggests another year close to or above the 2023 level. Older vintages have partially matured, so these are stock figures rather than annual issuance.

The left-hand panel, drawn from EBA reporting, shows who is on the other side of those transactions. Private credit funds are reported as the leading investor group, named by roughly a third of responding banks. Other investment funds, insurance companies, and pension funds account for another 45% between them, with a residual ~22% spread across asset managers, sovereign wealth funds, and other investor types.

This is where the FSB’s “circles of risks” language earns its plural. Some banks are simultaneously: financing private credit funds through credit lines; transferring loan credit risk to those same funds through SRTs; and holding revolving credit facilities with the corporates the PC funds are lending to. The motive for the SRT itself is regulatory capital relief — by transferring the credit risk of a loan book to outside investors, the bank reduces the risk-weighted capital it must hold against those loans. But when the same fund holds a bank’s SRT and receives that bank’s subscription financing — and the FSB acknowledges this is plausible but unquantified — the capital has been freed up while the economic exposure has not entirely left the bank–NBFI perimeter. The risk has been re-routed, not eliminated.

The supervisory response to this is hard. It requires look-through data that doesn’t currently exist at the regulatory level. The Eurosystem’s May 2026 paper identifies legal entity identifiers (LEIs) and a dedicated AIFMD subcategory for private credit funds as priority data infrastructure precisely to begin closing this gap. Until those are in place, the question of how much SRT risk is sitting inside fund vehicles that the same banks also finance is — to use the FSB’s own framing — a question.

Why supervisors still can’t see most of this

The FSB report’s data annex contains what I think is the most important chart in the entire document, even though it sits near the back. Redrawn above, it shows what data is available to authorities in each major jurisdiction, by data category.

The story is not, as I initially expected, “US sees everything, EA sees nothing.” Look at the columns. The euro area can fully see aggregate drawn exposures (top row, green) but only via ad hoc collection. Total commitments — including undrawn lines — are missing. Facility-type breakdowns are partial. Subscription lines, the most common form of bank-to-fund financing, are only partially reported. Revolving credit facilities, lending to offshore funds, and granular time series are largely missing.

Look at the rows. The categories where private credit risk could be most plausibly hidden — subscription lines, revolving facilities, offshore fund exposure, granular time series — are red or yellow in most jurisdictions, including in the US. Switzerland is blind to most of the granular facility metrics, with five of seven categories missing. The UK and the US are the strongest reporters among the jurisdictions shown, but neither is comprehensive.

This is the supervisory deficit made concrete. The implication for the wider NBFI argument is direct: if this is what data availability looks like for the segment that has just received a dedicated FSB report, the surveillance situation for the broader NBFI sector — hedge funds, MMFs, securitisation vehicles, derivatives exposures — is no better, and in many places worse.

The Eurosystem’s May paper makes the same diagnosis. It proposes three priority interventions: targeted amendments to AIFMD, the UCITS Directive and related legislation to enable data sharing between the ECB, ESRB, ESMA, and national supervisors; a centralised data access mechanism, with ESMA exploring a data hub as part of an integrated reporting framework; and mandatory use of LEIs across NBFI reporting, including for private credit funds. The paper also proposes amending ESMA’s AIFMD guidelines to introduce a specific AIF subtype for private credit funds — directly addressing the residual-category problem that today makes EU private credit hard to identify in regulatory data.

These are not glamorous proposals. They are plumbing. But they are the right plumbing to fix, and the FSB heatmap above is the diagnostic that makes the case for them.

What the FSB report is really about

The FSB report can be read in two ways. The narrower reading treats it as a specific assessment of a fast-growing asset class — useful, careful, not particularly novel. The wider reading, which I find more interesting, treats it as a diagnostic of NBFI supervision: a worked example of what we know and don’t know about a single segment of market-based credit intermediation, written by people who clearly understand the limits of their own evidence.

Finance Watch’s recent report on systemic risk from shadow banking makes the wider case explicitly. Banks and NBFIs, they argue, function as communicating vessels — connected via leverage, funding, securitisation, derivatives, and liquidity channels that supervisors only partially see. The FSB’s circles-of-risks language is the same point in narrower form. So is the Eurosystem’s proposal to build a centralised NBFI data infrastructure. So is the ESRB Advisory Scientific Committee’s reported consideration of a formal private credit inquiry.

What’s notable is that these efforts are converging. The diagnosis is broadly shared: NBFI is now a large enough share of global financial assets that supervising the banking system alone is no longer sufficient. The prescriptions are still being assembled — data infrastructure first, then macroprudential tools, eventually possibly entity-level designations of systemically important NBFIs.

Private credit is where the architecture is currently easiest to see in Europe. That is partly because it has grown fast, attracted political attention, and become the subject of a dedicated FSB report. It is also because — paradoxically — private credit’s interlinkages with banks are more visible than those of other NBFI segments, precisely because banks are involved at every step. The FSB report is therefore both an asset-class document and, more interestingly, a structural map.

Read it as the structural map. The risk of circular exposures is real. The data to confirm or refute the more concerning interpretations is not yet available. The Eurosystem is building the surveillance infrastructure that would make better answers possible. The recent publications suggest these theoretical risks are increasingly being viewed as supervisory priorities rather than abstract concerns.

What we are watching, in short, is the start of a wider NBFI supervisory framework being assembled — with private credit as the most legible test case.

Paweł Fiedor - The Macro Prudential View

The views expressed are the author’s own and do not necessarily reflect those of any institution with which the author is or has been affiliated.

Sources: FSB, Report on Vulnerabilities in Private Credit, 6 May 2026 — https://www.fsb.org/uploads/P060526.pdf; Eurosystem, Strengthening the macroprudential lens in the regulation of non-bank financial intermediation, May 2026 — https://www.ecb.europa.eu/press/intro/publications/pdf/ecb.ebaecb202605.en.pdf; ECB, Financial Stability Review May 2024, Special Feature C — https://www.ecb.europa.eu/press/financial-stability-publications/fsr/special/html/ecb.fsrart202405_03~bc23a48dbc.en.html; EBA, Risk Assessment Report Spring 2025; Berg and Lee, Measuring Counterparty Exposures to Private Credit, OFR Brief Series, March 2026 — https://www.financialresearch.gov/briefs/files/OFRBrief-26-02-measuring-counterparty-exposures-private-credit.pdf; Finance Watch, Systemic risk from shadow banking — https://www.finance-watch.org/policy-portal/stability-supervision/report-systemic-risk-from-shadow-banking/; Barron’s, “Europe’s Regulators May Launch Private Credit Inquiry,” — https://www.barrons.com/articles/europe-private-credit-probe-c22ea2dc.

Part 1 used twelve years of Bundesbank data to argue that Germany’s KAGB redemption-restriction regime materially compressed retail open-ended property fund flow stress, including through the 2022–24 European rate shock. The German evidence is empirical: did the template work? The Irish material here is institutional: how is the template being deployed in Europe right now, by whom, with what coordination, and against which gaps in the architecture?

The Eurosystem’s May 2026 report Strengthening the macroprudential lens in the regulation of non-bank financial intermediation proposes, among other things, a reciprocation framework for cross-border NBFI macroprudential measures. The institution that has built such a framework in practice is the Central Bank of Ireland. Discussion Paper 11, published 18 July 2023, sets out CBI’s conceptual foundation. Two policy deployments since then give two worked examples: leverage and liquidity measures for Irish-resident property funds in November 2022 (under Regulations 26 and 18 of the Irish AIFM Regulations), and a codified yield-buffer framework for Sterling LDI funds in April 2024 (under Article 25 AIFMD, in coordination with CSSF and aligned with TPR/FCA guidance for the UK leg).

CBI’s own press release on the LDI codification states explicitly that this was “the second time the Central Bank of Ireland has introduced policy measures under the non-bank pillar of its macroprudential policy framework” — the first being the property fund measures. That self-framing is useful: CBI is presenting both deployments as components of the same emerging architecture rather than as unrelated regulatory actions. This article takes that framing at face value and works through what each deployment looks like, what early data show, and what the two cases together say about the Eurosystem report’s reciprocation proposal.

The CBI framework architecture

DP11 articulates the conceptual case for a macroprudential perspective in fund-sector regulation that complements rather than replaces the existing investor-protection mandate. The paper is explicit on a point that matters for what follows: macroprudential policy for investment funds “will be most effective if regulators coordinate. This underpins the importance of developing a globally-consistent approach. In certain circumstances, domestic action may also be required.”

The two deployments illustrate both halves of that statement. Property funds were a domestic action: Irish-authorised funds and managers, an Irish commercial real estate exposure that posed Irish systemic risk. Sterling LDI was the coordinated case: vehicles domiciled across Ireland and Luxembourg, sterling-denominated exposures to UK pension liabilities, a crisis whose epicentre was the UK gilt market. The two cases bookend the operating range of the macroprudential framework CBI is building. What unites them is not identical legal machinery but the use of fund regulation for explicit financial-stability rather than investor-protection purposes — Regulations 26 and 18 in one case, Article 25 AIFMD in the other.

Property funds: the slow-moving case, three years in

CBI announced the property fund measures on 24 November 2022 with two components. First, a 60% total-debt-to-total-assets leverage limit, imposed by way of condition of authorisation under Regulation 26 of the Irish AIFM Regulations. Existing funds have a five-year implementation period running to 24 November 2027, during which CBI expects gradual and orderly progress toward lower leverage. New funds must comply from inception. Funds investing at least 80% of AuM in social housing are out of scope, subject to specific lease and debt-structure conditions.

Second, guidance on the application of Regulation 18 of the Irish AIFM Regulations setting an expected minimum liquidity timeframe of 12 months for property funds, given the nature of the underlying assets. Existing funds had an 18-month implementation period (the guidance applied from 24 July 2023); new funds authorised on or after 24 November 2022 must comply from inception.

These are textbook ex-ante macroprudential tools — a numerical leverage cap and a liability-side liquidity timeframe — applied to a cohort holding illiquid commercial real estate. The conceptual architecture is similar to KAGB but the policy instruments are different: KAGB used redemption restrictions on the liability side; CBI used leverage restrictions on the asset side combined with redemption-frequency guidance.

The chart above shows monthly net flows as % of lagged NAV for the Irish RE fund cohort from December 2014 to February 2026. Pre-Nov 2022 (95 monthly observations): mean +0.78%, σ 1.81%, 27% of months in net outflow. Post-Nov 2022 (40 monthly observations): mean +0.07%, σ 0.74%, 53% of months in net outflow. Flow volatility roughly halved; the upper tail of inflow surges has been eliminated.

The headline pattern is similar to the KAGB-era German case: post-implementation flow volatility compresses materially, and the tail risk on the inflow side is eliminated. The Irish post-2022 sample is shorter, the macro environment was specifically a CRE valuation correction rather than a broader retail-fund stress, and the dataset captures all Irish RE funds in the ECB Investment Fund Statistics rather than only the macroprudential cohort (≥50% Irish CRE), which CBI’s FSR 2025:II flags in footnote 64. With those caveats: the direction of travel is consistent with what the policy was designed to achieve.

The chart above decomposes the change in fund AuM into three components — net flows, valuation effects, and changes in borrowing — annualised across the pre and post periods. Pre-Nov 2022 the Irish RE fund sector grew by roughly €3.5bn per year, with flows (+€1.6bn), valuation (+€0.7bn), and borrowing (+€1.3bn) all contributing positively. Post-Nov 2022 the sector grew by €0.23bn per year, with modest inflows (+€0.41bn) offsetting CRE valuation drag (-€0.15bn) and effectively zero change in borrowing (-€0.02bn).

The post-implementation trajectory is neither the run-and-fire-sale dynamic the policy was designed to prevent, nor a continuation of pre-implementation growth. The sector neither grew nor contracted materially in the post-implementation period — a quieter trajectory than pre-2022. This is itself the policy story: in previous CRE cycles, falling valuations would trigger run-like dynamics on retail-facing vehicles, forcing asset sales that depressed valuations further. The fact that the sector has gone quiet against a meaningful CRE correction is the circuit-breaker working as intended. The bank-to-non-bank debt substitution within the cohort is worth flagging: CBI’s FSR 2025:II reports that Irish property fund debt fell over 2024 from €15.91bn to €15.07bn, with bank and other debt down €1.75bn partially offset by an increase of €0.91bn in non-bank debt (Chart 39). That is itself a within-cohort substitution worth monitoring as the leverage transition proceeds toward its November 2027 deadline.

The watch-this-space caveat: the most recent observation in the flow data is a -2.31% Pub-style outflow in December 2025, and the 12-month rolling volatility has crept from 0.50% to 1.19% over the past year. The leverage transition has two more years to run, and the funds adjusting toward the cap may be doing so against a still-soft CRE valuation environment. None of this is a problem with the policy — it is the policy doing its work, gradually, against a difficult macro backdrop. But it is a reminder that the post-implementation period is not yet a steady state.

Sterling LDI: the fast-moving cross-border case

The chart above shows UK 30-year gilt yields from 2020 to 2026, with policy milestones marked. The crisis itself was concentrated: the Bank of England’s December 2022 Financial Stability Report describes what happened in late September 2022 as “a vicious spiral of collateral calls and forced gilt sales that risked leading to further market dysfunction, creating a material risk to UK financial stability”. Nominal 30y gilts moved from 3.45% on 11 September to a 4.78% weekly close on 9 October — about 130 basis points in four weeks. The BoE’s emergency bond-purchase programme stabilised the market within roughly two weeks. The structural question — what to do with the LDI cohort thereafter — was the regulatory community’s to answer.

The response unfolded in two stages. On 30 November 2022, CBI and CSSF issued substantively identical industry letters to managers of GBP LDI funds, framed explicitly as a coordinated CBI/CSSF/ESMA response. The letters noted that resilience buffers in the 300–400 basis-point yield-shock range had been built up across the cohort post-crisis, expected those levels to be maintained, and required advance notification and stress-tested justification before any reduction. This was supervisory expectation backed by a notification regime — not a codified rule with an explicit numerical floor.

Eighteen months later, on 29 April 2024, CBI and CSSF announced aligned codified frameworks. The CBI version requires Irish-authorised GBP LDI funds to maintain resilience to a minimum 300 bps increase in UK yields, with a three-month transition for existing funds and at-inception compliance for new ones. The CSSF version is parallel: 300 bps minimum, monthly average yield buffer reported each month-end, with limited flexibility (one of the last four monthly observations may be below 300 bps in exceptional circumstances). The November 2022 letters formally ceased to apply once the implementation period ended on 29 July 2024.

CBI Governor Gabriel Makhlouf framed the rationale in terms that the Eurosystem report would later use almost verbatim: “The gilt market disruption of 2022 demonstrated how financial vulnerabilities in non-bank financial intermediation can amplify adverse shocks to the rest of the financial system and the broader economy. The macroprudential measures announced today aim to safeguard resilience of sterling LDI funds, and — in doing so — support financial stability at a global level. Given the cross-border nature of capital markets, achieving that outcome requires effective international co-ordination.” The cross-border coordination was explicit in the announcement: CBI worked with CSSF, UK authorities, ESMA “and relevant stakeholders since the beginning of the UK gilt market crisis”; the CSSF announced its aligned framework on the same day. The UK leg ran in parallel: the BoE FPC recommended interim TPR action; TPR’s April 2023 trustee guidance set a 250 bps minimum stress buffer plus scheme-specific operational buffer (principles-based rather than a single numerical floor); the FCA published associated guidance for fund managers.

The two architectures — CBI/CSSF’s 300 bps numerical floor with monthly observation, and TPR’s 250 bps minimum stress buffer plus principles-based operational buffer — are functionally similar approaches to a shared resilience objective. CBI/CSSF chose a single numerical floor that is straightforward to monitor and enforce. TPR chose a principles-based architecture that requires trustee judgement about scheme-specific exposures. Each architecture offers different operational trade-offs; the next stress event will provide the empirical comparison that published evidence does not yet allow.

The chart above shows the structural reason GBP LDI funds got macroprudential attention first. From ECB Macroprudential Bulletin Issue 26, Table 1 (Bouveret, Ferrari, Grill, Molestina Vivar, Schmidt and Weistroffer, 2025; cross-referenced with ESRB NBFI Risk Monitor 2025, Table 3): GBP LDI is the largest cohort by NAV (€67.8bn) within the EU’s substantially-leveraged AIF universe, the largest by absolute repo borrowing (€70.0bn), and concentrates its leverage in repo rather than derivatives. Among substantially-leveraged AIFs at end-2023, GBP LDI alone accounts for €349bn of AuM — by far the dominant single cohort.

Bouveret et al. (2025) test this cohort against the exact 300 bps shock the codified buffer is designed to absorb. They find an average NAV loss of 31% for GBP LDI funds and 26% for EUR LDI funds — described as having “negligible” effect on hedge funds and other leveraged AIFs at this risk factor. Crucially, the article reports that “only very few LDI funds would have a NAV below zero” in this scenario: the calibrated buffer absorbs the calibrated stress. A milder 100 bps shock generates a €6.6bn aggregate liquidity shortfall across the LDI cohort, which Bouveret et al. note “would be covered by the redemption of money market fund shares and sales of unpledged bonds”. That is the cross-border doom loop in compressed form: a UK gilt shock forces Irish and Luxembourg LDI funds to redeem MMF shares (which are themselves a major source of short-term funding for euro-area banks via commercial paper and certificates of deposit, as documented in ESRB monitoring of euro-area MMFs) and to sell unpledged bonds into thin markets. The calibration is intended to absorb the specified shock scenario; the secondary transmission channels remain relevant and are precisely the cross-border vector the Eurosystem report is trying to address.

What the two cases together say about the Eurosystem proposal

Two deployments, three years apart, one template. Both explicitly framed by CBI as components of the same emerging macroprudential architecture. Property funds: slower-moving, single-jurisdiction, multi-year transition. LDI: fast-moving, cross-border, 18-month codification with monthly compliance reporting. Both build on the existing AIFMD machinery — Article 25 in the LDI case, Regulations 26 and 18 of the Irish AIFM Regulations in the property fund case — but apply that machinery for explicit financial-stability rather than investor-protection purposes. That is the analytical point DP11 makes: macroprudential mandate complements the investor-protection mandate; both can be advanced through the same regulatory infrastructure.

For the Eurosystem report’s reciprocation proposal, this matters in two specific ways.

First, the LDI case shows what cross-border coordination looks like when it works. CBI did not act unilaterally — it acted in deliberate coordination with CSSF and ESMA, and the codified frameworks are aligned across the two domiciles. That coordination was effective but bilateral and ad hoc. Under the Eurosystem report’s proposed reciprocation framework, similar action would have a defined process at EU level rather than depending on bilateral goodwill and the personal coordination of senior NCA staff. The LDI case is the existence proof; the reciprocation framework is the institutional infrastructure that would let it scale.

Second, the property fund case illustrates the gap that reciprocation is specifically designed to address. Article 25 AIFMD is a mandate exercised by the AIFM’s home regulator over the funds it authorises. But Irish commercial real estate could be held by funds domiciled in multiple EU jurisdictions; if a substantial share of the addressable Irish CRE market is held by funds authorised outside Ireland, CBI cannot apply its leverage limit to those vehicles. Domestic action is constrained by where funds happen to be domiciled, even when the underlying systemic exposure is unambiguously domestic. Reciprocation — under which other NCAs would apply equivalent measures to the funds they authorise that hold material Irish exposures — is the institutional missing piece. It is also the piece that is hardest to achieve voluntarily, because the reciprocating NCA must balance domestic priorities alongside measures designed primarily to address a foreign systemic risk (a classic collective-action problem in EU macroprudential policy).

The Eurosystem proposal puts this missing piece on the institutional table. Whether the Commission’s eventual legislative response carries it through is a separate question. But the analytical case for reciprocation is now anchored in two concrete deployments that have run for three and one years respectively, both of which expose the same gap in the existing architecture. Twelve years of German evidence support the empirical case for ex-ante liquidity tools. Three years of Irish institutional building support the case for the cross-border framework needed to deploy them at EU scale.

These cases make the implementation problem concrete.

Paweł Fiedor - The Macro Prudential View

Sources and methodology

Eurosystem and ECB

ECB (May 2026), Strengthening the macroprudential lens in the regulation of non-bank financial intermediation. Eurosystem report.

Bouveret, A.; Ferrari, M.; Grill, M.; Molestina Vivar, L.; Schmidt, D. J.; Weistroffer, C. (2025), Leveraged investment funds: A framework for assessing risks and designing policies. ECB Macroprudential Bulletin, Issue 26.

ESRB (2025), EU Non-bank Financial Intermediation Risk Monitor 2025, Table 3.

CBI

Discussion Paper 11 – An approach to macroprudential policy for investment funds, 18 July 2023.

The Central Bank’s macroprudential policy framework for Irish property funds, November 2022.

Industry letter: Liability Driven Investment Funds, 30 November 2022.

Central Bank introduces macroprudential measures for Irish-authorised GBP-denominated LDI funds, 29 April 2024.

Financial Stability Review 2025:II, Chart 39 and footnote 64.

Other regulators

Bank of England (December 2022), Financial Stability Report.

CSSF (29 April 2024), Macroprudential measures for GBP Liability Driven Investment funds.

ESRB (2021), Issues note on systemic vulnerabilities of and preliminary policy considerations to reform money market funds — referenced for the MMF-to-bank short-term funding channel.

The Pensions Regulator (April 2023), guidance on the use of leveraged liability-driven investments by trustees of defined benefit pension schemes.

Data

ECB Investment Fund Statistics (IVF) — Irish RE funds, monthly series.

Investing.com UK 30-year bond yield (nominal, weekly close).

Bank of England yield curves — real 30-year spot curve, daily.

Calculations. All flow statistics, decompositions and rolling volatility measures for the Irish property fund section are computed by The Macro Prudential View from the ECB IVF monthly series. Pre period: December 2014 to October 2022 (95 monthly observations). Post period: November 2022 to February 2026 (40 monthly observations) for flow statistics; November 2022 to November 2025 (37 monthly observations) for the AuM decomposition, because IVF Total Assets is missing for December 2025 to February 2026 and including those months would break the additive identity (Δ AuM = Net flows + Valuation + Δ Borrowing). Working spreadsheet available on request.

Views are my own. This article is a personal analytical piece based on public sources. It does not represent the views of the European Systemic Risk Board, the Central Bank of Ireland, the Eurosystem, or any other institution.

The Eurosystem’s May 2026 report Strengthening the macroprudential lens in the regulation of non-bank financial intermediation proposes a familiar set of structural tools for retail open-ended fund liquidity risk: minimum holding periods, redemption notice periods, leverage caps. The analytical framing is forward-looking — what an EU-wide macroprudential framework for investment funds should look like. The empirical question is backward-looking: where has anything resembling this template been deployed before, and what happened?

The closest publicly observable analogue is Germany. The Kapitalanlagegesetzbuch (KAGB), in force from 22 July 2013, imposed a 24-month minimum holding period and a 12-month redemption notice on retail open-ended property funds (Publikumsfonds, or retail OEIFs — abbreviated Pub in the analysis below) but did not apply these restrictions to institutional open-ended property funds (Spezialfonds, abbreviated Spez). That asymmetry, sustained for twelve years, gives us a useful cohort comparison with monthly data publicly available from the Bundesbank’s time-series database. The 2022–24 European interest-rate shock has, additionally, given the regime its first substantive post-implementation stress test.

This article works through what twelve years of public data say about whether the template stabilises retail OEIF flow dynamics. The headline finding is supportive: post-KAGB Pub flow volatility is roughly half its pre-KAGB level, the upper tail of inflow surges has been eliminated, and the 2022–24 rate shock — which produced 62% of months in net outflow in the treated cohort — saw a worst single-month outflow of -0.75% of NAV, an order of magnitude smaller than the -5.6% the same cohort experienced in October 2008. The institutional comparison cohort, which faced the same macro environment without the same redemption restrictions, behaved very differently in both episodes. The empirical case for the toolset is materially strengthened by the German experience; the constraints on generalising it remain real.

The template, the policy, the cohort

The 2008 financial crisis exposed a specific structural fragility in German retail open-ended property funds. The funds offered daily redemption rights against an underlying portfolio of commercial real estate — a textbook liquidity mismatch. When investor confidence broke in autumn 2008, the funds had no choice but to suspend redemptions: Schnejdar, Woltering, Heinrich and Sebastian (2022) document nine retail OEIFs suspending redemptions in October 2008 alone, including KanAm Grundinvest, AXA Immoselect, SEB ImmoInvest, Morgan Stanley P2 Value, CS Euroreal and DEGI International. “By August 2012, all closed funds were forced to announce their liquidations” under the suspension rules then in force.

The KAGB’s 2013 redemption restrictions were the policy response. From 22 July 2013, new investors in retail open-ended property funds could not redeem within 24 months of subscription, and any redemption thereafter required 12 months’ notice. The intent was to better match the liquidity profile of the liability side to the underlying asset class. The same restrictions did not apply to Spezialfonds, the institutional vehicle, which serves professional investors — typically pension schemes, insurance undertakings and corporate treasuries — and operates with negotiated rather than daily redemption terms. Crucially, this means Spez and Pub differ structurally beyond just the KAGB rules: investor base, redemption terms, and to some extent portfolio composition diverge across the cohorts. That is why this analysis treats Spez as a comparison benchmark rather than a true counterfactual.

That regulatory asymmetry, in place since 2013, is what allows the analysis. Both cohorts hold broadly similar underlying assets — German and European commercial real estate. Both experienced the same macro environment. Only one had the redemption restrictions applied to its retail liability structure. The question becomes empirically tractable.

The empirical strategy

This article defines five regimes. Pre-Crisis covers 2000 to 2007: post-euro adoption, pre-shock. Crisis covers January 2008 to July 2013: the wave of suspensions and the run-up to KAGB. Post-KAGB calm covers August 2013 to December 2021: the period during which both cohorts operated under the new rules in a low-rate, generally calm macro environment. Post-KAGB rate shock covers 2022 to 2026: the period during which the European Central Bank raised the deposit facility rate from -0.5% to 4.0% between July 2022 and September 2023, and German commercial real estate valuations corrected meaningfully thereafter. Pre-2000 data is omitted because of the DM-EUR conversion in January 1999, which mechanically distorts level comparisons.

Data come from the Bundesbank’s open-ended-investment-fund statistics — specifically the Net Asset Value, loans-received and net-flow series for both Pub and Spez cohorts. Commercial real estate valuation context comes from the vdp Property Price Index. All series are publicly available and monthly. The Bundesbank series is in DM through December 1998 and EUR thereafter, which is why pre-2000 observations are excluded from the analysis. Note that all percentage values, regime statistics, leverage averages and decompositions in this article are calculated by The Macro Prudential View from the public Bundesbank series; methodology is detailed in the sources section at the end.

The master finding: flow volatility

The chart above shows monthly net flows as % of lagged NAV for both cohorts from 2000 to 2026. Post-KAGB Pub flow volatility is structurally lower than pre-KAGB Pub flow volatility — and structurally lower than the institutional comparison cohort over the same period. Pre-Crisis monthly net-flow standard deviation for Pub was 1.53% of prior-month NAV. Crisis-era it dropped to 0.95%, but the worst single month was -5.6% in October 2008 — that is the run dynamics, the single-month redemption pressure that triggered the suspensions. Post-KAGB calm: σ falls to 0.50%, with only 6% of months in net outflow. Post-KAGB rate shock: σ falls further to 0.39%, but with 62% of months in net outflow.

That last regime is the most informative one. The 2022–24 European rate shock was the first genuinely adverse macro environment the post-KAGB regime had to absorb. CRE valuations fell — the vdp office capital-value index dropped from a 2022 peak of around 188 to around 156 by mid-2024, a near-17% correction in commercial property values. Retail investors in German open-ended property funds responded: 62% of months from January 2022 onward saw net outflows. But the magnitude per month was small. The worst single month was -0.75% of NAV. The same cohort in 2008 had a worst month of -5.6%. The redemption-restriction architecture appears to have shaped what investors could do: they could subscribe freely; they could leave but only with notice; the resulting flow trajectory looks like a slow drift rather than a run. Mechanically, the 12-month notice period caps the rate at which any individual subscription can exit, converting what would otherwise be a stampede into a managed queue with a one-year runway for the fund to manage cash buffers and execute property sales.

The institutional comparison cohort tells a complementary story. Spezialfonds had a worst single month in the Crisis era of -2.6% (March 2008) — about half the magnitude of the contemporaneous Pub episode. In the post-2022 rate shock, Spez had zero months of net outflow. Same shock, very different response. The cohort with negotiated rather than daily redemption terms did not exhibit the same run-like dynamics; the structural mismatch was lower to begin with. It is also worth noting that the policy did not eliminate retail demand for liquidity — investors with immediate-exit needs continued to be able to sell their fund shares on secondary venues such as the Hamburg exchange’s Fondsbörse Deutschland at a discount to NAV, shifting the cost of liquidity from the fund’s balance sheet (where it would force asset fire sales) to the exiting investor. Gerlach and Maurer (2020) document the secondary-market dynamics in detail, showing that “OREF shares are traded at a discount on secondary markets when the fund management suspends the redemption of shares or when the fund is being liquidated” — i.e., the secondary market prices the trapped-liquidity risk explicitly, leaving the underlying fund balance sheet intact.

The chart bove distils the same finding to summary statistics across the four post-2000 regimes. Pre-Crisis, the two cohorts looked quantitatively similar — Pub σ of 1.53%, Spez σ of 1.83%, neither with extreme outflow months. Crisis era split them: Pub took the run dynamics, Spez did not. Post-KAGB calm: both cohorts compressed, with Pub at the lower stress level. Post-KAGB rate shock: Pub stress remained reduced even though 62% of months were in outflow, because each individual month’s outflow was small. The right-hand panel — worst single-month outflow by regime — shows the monotonic pattern most clearly. Pub: -5.4%, -5.6%, -1.7%, -0.75%. Spez over the same regimes: -0.7%, -2.6%, -0.5%, +0.0%. Same data, same broad asset class, different stress profile depending on whether the redemption-restriction architecture is in place. (Regime labels here are analytical sample partitions, not official supervisory classifications.)

Sectoral substitution

A separate observation, less prominent in the policy debate, is shown in the chart above: Spez NAV overtook Pub NAV in December 2017. From end-1993 to end-2025, Pub NAV grew about 2.5×; Spez NAV grew about 63×. The sector now sits at roughly €112bn of retail and €179bn of institutional NAV (latest available data, end-2025). The two trajectories are different vehicle types serving different investor classes, but they hold broadly comparable underlying assets — institutional scale has overtaken retail scale within the same broad German CRE fund universe.

This is genuinely ambiguous. One reading is that the KAGB redemption restrictions made the retail vehicle less attractive to investors who wanted liquidity, displacing money toward the institutional channel. Another reading is that the institutional CRE allocation grew secularly across the post-2010 period for reasons entirely unrelated to KAGB — German pension funds and insurance undertakings deploying duration-matched property allocations in a low-rate world, a trend visible across continental Europe regardless of OEIF regulation. The Bundesbank time series alone cannot separate these two explanations.

What it can say is that the redemption-management regime did not destroy the German CRE fund channel. Total NAV across both cohorts is higher than at any pre-2013 point. The institutional channel’s growth replaced the retail channel’s growth, but the function — providing intermediated CRE exposure — continued. For the Eurosystem proposal, this matters: the most concrete worry about ex-ante liquidity tools is that they push activity out of the regulated channel rather than reducing the underlying mismatch. The German evidence does not support that worry strongly, though the substitution toward institutional vehicles is consistent with a softer version of it.

Liability-side risk reduction

The chart above shows that both cohorts deleveraged from mid-2000s peaks. Pre-KAGB averages: Pub 1.16, Spez 1.33. Post-KAGB averages: Pub 1.10, Spez 1.26. Pub now operates at structurally lower leverage; Spez also moved down but remains higher.

This is not cleanly attributable to KAGB. Both cohorts deleveraged, in roughly parallel trajectories, suggesting macro factors — interest rates, supervisory pressure, generalised risk aversion through the 2008–2014 period — affected both. KAGB plausibly contributed to the lower steady-state Pub level, particularly as the regime took hold and new fund launches operated under the new rules from inception. But isolating the KAGB-specific contribution from the broader deleveraging would require fund-level data and a more demanding identification strategy than the cohort comparison provides.

What the chart does show is that the liability-side risk reduction the redemption-management regime was meant to encourage occurred. Pub funds today carry less debt against NAV than they did pre-Crisis. The 2022 rate shock produced a small uptick — visible at the right edge of the chart — that is worth monitoring but has not undone the post-KAGB structural shift.

What this means for the Eurosystem proposal

The German evidence supports the empirical proposition that ex-ante OEIF liquidity tools — minimum holding periods, redemption notice periods — stabilise retail OEIF flow dynamics in the face of substantial macro stress. The 2022–24 rate shock is the relevant validation: it occurred under the post-KAGB regime, with European CRE valuations correcting by mid-double digits, and the treated cohort absorbed it through a slow drift in flows rather than the run dynamics that defined 2008. Twelve years of post-implementation data, including a real-world adverse regime, suggest the redemption-management toolset works in this context.

Three constraints on inference are worth flagging. First, the German cohort was already moving toward institutional dominance through the 2010s, for reasons partly independent of KAGB. The substitution between Pub and Spez may be larger than the data alone can attribute to the policy. Second, the 2022–24 period was a rate shock with associated CRE valuation stress, not a pure redemption run; the KAGB regime has not yet been tested by a fast-moving liquidity event of the September 2022 gilt-crisis variety. The German evidence is about whether the toolset handles slow stress, not whether it handles sudden stress. Third, the cohort definition — German retail open-ended property funds — is narrower than the Eurosystem report’s proposed scope. Generalising to other markets and structures should be tested case-by-case rather than assumed.

Net: the empirical case is positive enough to support the report’s direction. The German data make it difficult to dismiss the proposition that ex-ante liquidity tools can work in practice. The lighter version of the question — do they work in all the markets and structures the report covers? — remains open and worth investigating case-by-case.

Paweł Fiedor - The Macro Prudential View

Part 2: Ireland’s CBI deployed analogous measures twice in three years — to property funds in 2022 and Sterling LDI in 2024 — providing the first cross-country test of how the template generalises.

Sources and methodology

ECB (May 2026), Strengthening the macroprudential lens in the regulation of non-bank financial intermediation. Eurosystem report.

Schnejdar, Sebastian; Woltering, René-Ojas; Heinrich, Michael; Sebastian, Steffen (2022), Fund Closure Risks of Open-End Real Estate Funds. Journal of Real Estate Research.

Gerlach, Patrick; Maurer, Raimond (2020), The Growing Importance of Secondary Market Activities for Open-end Real Estate Fund Shares in Germany. Schmalenbach Business Review 72, 65–106.

Deutsche Bundesbank, Investment companies time-series database — open-end investment companies, real estate sector. Public monthly series for both Publikumsfonds and Spezialfonds, covering Net Asset Value, loans received from financial institutions, and net flows.

vdp Property Price Index, Verband deutscher Pfandbriefbanken (Q1 2003 – Q4 2025) — office capital values used for CRE valuation context.

ECB key interest rates — deposit facility rate series for the 2022–23 ECB tightening cycle.

Calculations. All percentage values, regime statistics, leverage averages and decompositions are computed by The Macro Prudential View from the Bundesbank monthly series. Monthly net flow as % of NAV is calculated as net flow in month t divided by NAV at end of month t-1, multiplied by 100. Standard deviation is the sample standard deviation of monthly flow %s within each regime. Leverage is calculated as (NAV + loans received) / NAV. Pre/post-KAGB averages use 22 July 2013 as the regime break, with August 2013 as the first full post-KAGB month. Pre-2000 observations are excluded throughout because of the DM-EUR conversion in January 1999, which mechanically distorts level comparisons. Working spreadsheet available on request.

Views are my own.

In April 2025, US Treasuries did something they were not supposed to do. The administration’s tariff announcements triggered a sharp equity sell-off — the kind of move that, for a generation, had been the cue for Treasury yields to fall as global capital rotated toward the world’s safe asset. Instead, long-dated yields rose. Bonds and stocks sold off together. The convenience yield embedded in Treasuries — the premium markets pay for “moneyness,” for the property of being valued at face value without anyone asking awkward questions — measurably contracted. Whatever was happening, it was not the textbook safe-haven response.

The episode was not a one-off. The correlation between Treasury and equity returns has been drifting positive since the Fed began tightening in March 2022, and has spent meaningful stretches above zero ever since. The asset that anchors the global financial system has become a regime-dependent hedge — sometimes safe, sometimes not, increasingly conditional on whether anyone has tightened recently or sprung a fiscal surprise.

A few weeks short of the first anniversary of that tariff shock, the European Systemic Risk Board hosted a joint workshop of its Advisory Technical Committee and Advisory Scientific Committee on “A European Safe Asset and Financial Stability.” Olli Rehn’s welcome address framed the question against precisely this backdrop: geopolitical fragmentation, the financing needs of European public goods, the international role of the euro. Philip Lane’s keynote walked the technical landscape — three broad routes to expanding euro safe-asset supply, each with different design properties and different political preconditions.

The debate has shifted. The question is no longer whether Europe needs more safe assets. It is which design produces them, at what cost, with what residual safety properties — and whether the entire concept of a “safe asset” still means in 2026 what it meant in 2011, when the original European Safe Bonds (ESBies) proposal was first published.

This piece works through the empirics and the design space. Five charts, four design families, one question that turns out to be more complicated than it sounds: what does it actually mean to be safe?

The shortage

Start with the volumes, because they are stark.

Euro-denominated marketable central government and supranational debt totals roughly €12.5 trillion at end-April 2026. Across all rating tiers — from German Bunds to Greek GGBs, from EU NGEU bonds to ESM and EFSF — that is the entire potentially-safe stock available to the euro area. By comparison, US marketable Treasuries total around $30.8tn at end-March 2026, or €26.3tn at the prevailing exchange rate. The euro stock is roughly 47% of the size of the US benchmark.

Cut to strict AAA — the rating that would, in principle, anchor the system — and the picture sharpens. Germany, the Netherlands, Luxembourg, plus the AAA-rated supranationals (the EU at S&P AA+ but Aaa/AAA at the other three majors; EIB, ESM, CEB, EBRD all clean AAA) sum to about €3.6tn. That is roughly one-seventh the size of the US Treasury market.

Even on a more permissive cut — AAA plus AA, putting France in the AA bucket on the basis of Moody’s Aa3 (S&P and Fitch downgraded France to A+ in 2025) — the total reaches €7.4tn. Still well under a third of the US benchmark.

The composition makes it worse. The bulk of euro-denominated sovereign issuance is rated A or BBB: Italy at €2.6tn dominates the BBB tier; Spain, Belgium, Portugal and the smaller member states populate the A tier. Around 40% of the euro safe-asset universe is below AA. That is not a structural feature you can engineer your way out of by issuing more national bonds.

This is what Lane refers to as the structural undersupply of “safe-asset services” — and what the supranational layer (NGEU, EU bills, EIB issuance, the ESM/EFSF stack) has been quietly trying to address since 2010. EU-Bonds outstanding now sit just over €700bn, of which roughly €450–500bn is NGEU-related, with the borrowing window closing at end-2026 and repayments beginning from 2028. Without successor programmes, the EU bond stock will start shrinking just as the structural arguments for a larger one intensify.

Is anything safe in 2026?

The shortage is real. But it is also worth asking what, exactly, is in short supply.

Lane’s keynote followed the standard working definition in the literature: a safe asset is highly liquid and appreciates in relative value under stress. The formulation packs three distinct properties into one phrase. Credit safety: the issuer pays. Market liquidity: holders can transact at low cost in size, including under stress. Hedging: the asset gains value when other things fall, so it offsets portfolio losses. The full definition requires all three. Failure on any one dimension means the asset is not, by Lane’s own standard, fully safe.

The textbook reference points all clear the credit dimension comfortably. None of them clears all three reliably.

US Treasuries are the obvious case. The chart shows the rolling 26-week correlation between weekly returns on the 7–10 year Treasury ETF and the S&P 500 since 2009. The classic safe-haven property — Treasuries rising when equities fall — produces a negative correlation. Through the 2010s, the correlation sat consistently between –0.3 and –0.7. From 2022 onward, it inverted. Annual averages turned positive in 2023 and 2024. The April 2025 tariff shock, the SVB/Credit Suisse moment in March 2023, and the broader inflation-shock regime have all coincided with episodes where Treasuries failed to hedge.

Darrell Duffie’s recent JEP piece attributes this to a combination of dealer balance-sheet constraints, fiscal trajectory, and regulatory capital limits compressing intermediation capacity at exactly the moments when liquidity provision matters most. The credit dimension is intact — the US is one notch below AAA at all three majors after Moody’s downgraded to Aa1 in May 2025 (S&P and Fitch are at AA+), but no one is pricing actual default risk. The breakdown is in liquidity and hedging, the second and third dimensions of Lane’s definition. None of this changes the fact that Treasuries still dominate other sovereign assets in scale and breadth of usage. The hierarchy is not gone; it is just less reliable than it was.

The other pillars look no better when scrutinised on the same three dimensions.

Bunds function as a regional rather than global safe asset, anchoring euro-area portfolios but not (in the way Treasuries do) global ones — a point established empirically in the ECB’s recent work on bond substitution patterns. Germany’s fiscal turn since 2023, with the constitutional debt brake reform and ramped defence and infrastructure spending, has not threatened the AAA rating but has materially altered the supply-and-demand framing.

Gilts, in 2022, demonstrated that an asset can pass the credit test cleanly and still fail the market-functioning test. The Bank of England’s anatomy of the LDI crisis documents how liability-driven investment unwinds drove extreme moves in long-dated gilts despite no shift in UK creditworthiness. The asset was safe; the market was not.

JGBs are the inverse case: credit fine, liquidity impaired by years of BoJ purchases. As FRBSF research and AMRO’s 2025 work document, the BoJ’s footprint has hollowed out functioning JGB markets even as it tapers; the liquidity premium has risen, and the question of who replaces the central bank as marginal holder remains open.

The synthesis is uncomfortable but unavoidable. The frame established by Gorton (2017) — safe assets as instruments “always valued at face value without expensive information production” — was always context-dependent. What counted as safe in 2011 is not what counts as safe in 2026. None of the four canonical sovereign safe assets currently passes all three of Lane’s dimensions across all regimes. Safety has become contingent, regime-dependent, and dependent on the institutional and market-structure context surrounding each asset.

This sharpens the European policy question rather than dulls it. A diversified, properly engineered safe asset has the potential to be more robust on at least one of these dimensions — diversification protects against single-issuer fiscal trajectories, single-jurisdiction market structure failures, or single-central-bank footprints. The rest of this piece works through what the engineering options actually look like.

Three reform paths — and the status quo

Lane’s keynote walked through three broad routes to expanding euro safe-asset supply, alongside the implicit baseline of continuing with what we have. Each rests on a different combination of financial engineering, fiscal commitment, and political appetite.

The four designs differ not just in volume but in the kind of safety they deliver and the political capital they consume:

• The status quo continues the trajectory that began with banking union in 2014 and accelerated with NGEU in 2020. Banking union, ESM standing facility, TPI/OMT, NGEU borrowing — all of these have, incrementally, expanded the supranational safe-asset layer. The mechanism is institutional: build credibility and capacity at the European level, issue more bonds against it. It produces the existing fragmented stock by rating tier (€12.5tn total, €3.6tn AAA), and it keeps producing more — NGEU alone added several hundred billion in high-quality supply over five years. The precondition is continued institutional commitment.

• SBBS / ESBies — the proposal advanced by Brunnermeier, Langfield, Pagano, Reis, Van Nieuwerburgh and Vayanos (2017) and developed in detail by the ESRB High-Level Task Force on Safe Assets in 2018 — pools euro-area sovereign bonds in capital-key weights. A special-purpose entity issues two tranches against them: a senior tranche (typically 70% of face value), which serves as the area-wide safe asset, and a junior tranche (the remaining 30%), which absorbs first losses. No mutualisation: each member state continues to service its own debt. The senior tranche’s safety comes from diversification and subordination, not from joint guarantees. The precondition is regulatory — a Commission proposal in 2018 stalled, but the technical work is largely complete.

• Blue bonds, in Olivier Blanchard and Ángel Ubide’s 2025 PIIE proposal, take the opposite direction. Convert each member state’s debt up to 25% of GDP into jointly-issued senior bonds, with each member ring-fencing a tax stream (VAT being the canonical example) to service its share. The output is roughly €5tn of senior, jointly-marketed paper — the largest single design by far, comparable in scale to the German Bund market. The precondition is durable political commitment to ring-fenced revenues and a credible legal architecture for the senior claim. Mutualisation is limited but real: individual rather than joint-and-several guarantees, but a much closer version of common debt than anything in the status quo.

• The national strategy — the path advocated by Bruegel — argues that scaling existing supranational issuance and pursuing fiscal reforms to upgrade individual sovereigns toward AAA could deliver more usable safe-asset stock than tranching or blue bonds in the medium term. No new instrument. The mutualisation profile is identical to the status quo — existing supranational mechanisms continue, just at larger scale. The output is incremental.

Hanno Lustig’s argument deserves to be heard on this point. Lustig’s analogy is to the United States in the 1840s: state defaults were politically wrenching but ultimately disciplinary, contributing to the constitutional balanced-budget rules that anchor American state finance today. Europe, by contrast, has consistently chosen the bailout-and-ECB-balance-sheet path. Joint debt without binding fiscal constraints, in Lustig’s reading, is not a Hamiltonian moment — it is a deferral. The moral hazard concern is not about the design itself but about whether the supporting fiscal architecture can hold. Lustig’s argument applies most directly to blue bonds, where the senior claim relies precisely on the durability of national tax-revenue ring-fences over multi-decade horizons.

These four paths are genuinely different on every dimension that matters. They produce different volumes (incremental versus €1tn versus €5tn versus open-ended). They require different preconditions (institutional continuity versus regulatory enabling act versus political tax-pledge commitment versus fiscal discipline). They imply different degrees of mutualisation (existing only, none, limited individual guarantees, existing only). And they leave different residual risks for the domestic financial system.

The doom loop hasn’t gone away

Why does this matter beyond the academic case for more diversified safe assets? Because the bank-sovereign nexus that motivated banking union in the first place has not weakened.

The chart plots holdings of domestic government debt by commercial banks (MFIs excluding the ESCB, so stripping out PSPP and PEPP holdings on the central-bank side) as a share of total bank assets, monthly since 2010. Six countries: the four major peripherals — Italy, Spain, Portugal, Greece — and France and Germany as core comparators.

The data tells a sharper story than the institutional reform narrative would suggest. Italian banks hold around 10% of their assets in Italian government debt, with the all-time peak — 12% — reached in August 2020, during the COVID-era issuance surge. Greek banks rebuilt their domestic exposure from near-zero post-PSI to 9.7% by January 2025 — also an all-time high. Spanish banks have sat in the 7–9% range for over a decade. Only Portugal shows a clear de-risking, from a 9.4% peak in 2019 to 4.6% currently. France is creeping up. Germany is the only country meaningfully below its 2010 starting point.

OMT (July 2012) and the SSM (November 2014) are marked on the chart. Neither has materially bent the trajectory of any line. The 2012 Greek PSI is also visible — it is the only intervention on the chart that produced a structural break, and the cliff in the Greek line shows it. Twelve years of European banking-union architecture has not, on its own, produced a comparable structural break in any other country.

This is the macroprudential case for some safe asset, regardless of which design wins. Domestic banks in the periphery hold ten percent of their balance sheets in their own sovereign — and this share is at or near multi-decade highs. A genuine area-wide safe asset, held in place of concentrated domestic exposure, would mechanically dilute this concentration. The status quo has not resolved this problem; in some countries it has coincided with record exposures over the past five years.

What financial economics says about tranching

Of the three reform paths, SBBS / ESBies is the design where financial economics has the most to say. Blue bonds and the national strategy both turn on questions of political commitment and fiscal discipline that economic analysis can illuminate but not resolve. SBBS turns on a structural property of pooling and subordination that can be calibrated, simulated, and stress-tested.

The chart reproduces the benchmark calibration from Brunnermeier et al. (2017), Tables 3 and 4. The numbers are five-year expected losses on individual sovereigns and the engineered tranches.

The headline result: under the benchmark calibration, the senior tranche of a 30%-subordinated, GDP-weighted euro-area sovereign pool has a five-year expected loss of 0.09%. The safest individual sovereign, Germany untranched, has an expected loss of 0.13%. Tranching, applied to a diversified pool, produces an asset safer than any of its underlying components — without any mutualisation between member states.

The mechanics are not mysterious. The pool is GDP-weighted, so no single sovereign dominates. The senior tranche only takes losses once cumulative losses on the underlying pool exceed 30% — and given even modest correlation assumptions, the probability of cumulative euro-area sovereign losses breaching that threshold within five years is very small. The junior tranche absorbs the residual. The cross-check holds: 70% × 0.09% senior + 30% × 9.10% junior = 2.79%, exactly the GDP-weighted pool’s expected loss before tranching. The engineering is conservation of risk, not its disappearance.

A note on vintage: the Brunnermeier calibration uses December 2015 sovereign ratings. Since then, several sovereigns have moved — upgrades for Greece, Italy, Spain and Ireland; downgrades for France, Belgium, and others. A cross-check using S&P’s 1993–2024 historical local-currency sovereign default rates by rating bucket and current ratings yields a five-year pooled-portfolio expected loss of approximately 0.21% — well below Brunnermeier’s 2.79%. The difference reflects Brunnermeier’s use of stress-conditioned forward-looking PDs versus S&P’s unconditional realised rates. The benchmark calibration is therefore conservative. Under more benign assumptions, the senior tranche’s safety properties only improve.

This is what Lane meant by “safe-asset services.” A senior SBBS tranche, by construction, has credit risk lower than any individual euro-area sovereign. It has the regulatory tractability that comes with a single instrument standardisable across jurisdictions. And it has the structural diversification that matters in 2026: no single fiscal trajectory, no single market microstructure, no single central bank footprint determines its safety properties. The dimensions that Treasuries, Bunds, gilts, and JGBs each fail in their own way — the senior tranche, by construction, is more robust against them all.

Synthesis and open questions

Five charts and four designs into this article, what does the analytical case look like?

The shortage is real. Euro-denominated marketable central government and supranational debt is roughly half the size of the US Treasury market, and the strict-AAA subset is a seventh. The composition is heavily weighted toward A and BBB sovereigns. The supranational layer is currently growing but is structurally programmed to peak in 2026 and shrink from 2028 unless successor programmes are agreed. This supply cliff arrives at the same time as the ECB’s balance-sheet normalisation, with private markets absorbing more sovereign debt as the central-bank footprint shrinks.

The case for more safe-asset supply is reinforced, not weakened, by the observation that “safety” is contingent and multi-dimensional in 2026. Existing global benchmarks — Treasuries, Bunds, gilts, JGBs — each fail at least one of Lane’s three dimensions in some regime. A diversified, structurally engineered euro safe asset has different failure modes than any single-sovereign benchmark. That is not a marginal advantage in a world of fragmentation, geopolitical shocks, and divergent monetary policy paths.

The bank-sovereign nexus has not weakened, twelve years into banking union. Italian and Greek banks now sit at all-time-high domestic sovereign exposures, hit in 2020 and 2025 respectively. SBBS, by construction, dilutes this concentration without requiring any sovereign to cede fiscal sovereignty.

On the engineering, the financial economics is robust. A senior tranche of a diversified, capital-key-weighted euro-area sovereign pool, with 30% subordination, has a five-year expected loss lower than Germany untranched. The result holds under both the conservative Brunnermeier calibration and the more benign historical-default cross-check. No mutualisation is required. No fiscal commitment beyond the existing one is required. The precondition is a regulatory enabling act that the Commission has already drafted and that has been on the European policy shelf since 2018.

What the analysis cannot resolve is the political question. Blue bonds promise the largest stock — €5tn — but at the highest political cost: durable national tax-revenue ring-fences and individual guarantees backing a senior pool that legally subordinates remaining national debt. Lustig’s moral-hazard concern, transposed from the American 1840s, is that joint debt without binding fiscal discipline is unstable. The national-strategy path requires a degree of sustained fiscal consolidation that has historically proven difficult to maintain across multiple electoral cycles. The status quo continues to produce supranational issuance, but at a pace that may not match the volume Lane and Rehn argue is needed.

There are also things financial economics cannot tell us. Whether investors will buy the junior tranche of an SBBS structure at sustainable yields is an empirical question — it has not been tested at scale, and the ESRB HLTF’s 2018 survey of market participants found stronger interest in the senior tier than the junior. Whether the senior tranche, even at 0.09% expected loss, receives AAA-equivalent treatment for bank capital and ECB collateral purposes depends on regulatory choices that have not been made — and it is one of the choices the 2018 Commission proposal was designed to enable. Whether Europe’s political appetite for any of the three reform designs has materially changed since 2018 is a question about institutions, not models.

Lane’s keynote suggests that the technical groundwork for the main designs is largely in place. The ECB has been building adjacent infrastructure for the euro’s international role — TPI for managing sovereign-spread fragmentation, the expanded EUREP facility providing euro liquidity to non-euro-area central banks — but the safe asset itself remains the missing piece.

The 2018 ESBies proposal stalled because the volumetric and macroprudential urgency was not yet sufficient to overcome the political friction. The numbers in this piece — €3.6tn AAA stock, doom-loop exposures at multi-decade highs, the continuing erosion of the global safe-asset hierarchy — suggest the calculus may be different in 2026.

Paweł Fiedor - The Macro Prudential View

The views expressed here are personal and do not represent the views of the European Systemic Risk Board.

Charts compiled from: Brunnermeier, Langfield, Pagano, Reis, Van Nieuwerburgh and Vayanos, “ESBies: Safety in the tranches”, Economic Policy 32(90), 2017; Blanchard and Ubide, “Now is the time for Eurobonds: A specific proposal”, PIIE, 2025; the ESRB High-Level Task Force on Safe Assets, 2018; Bruegel, “Don’t look only to Brussels to increase the supply of safe assets in the EU”; Lustig, “Blue Bonds in Europe”, The Two Cents; Duffie, “How US Treasuries Can Remain the World’s Safe Haven”, Journal of Economic Perspectives, 2025; Gorton, “The History and Economics of Safe Assets”, NBER Working Paper, 2016; Bank of England, “An anatomy of the 2022 gilt market crisis”, 2023; the European Commission’s EU as an issuer page; national debt management offices for sovereign bond and bill stocks (Deutsche Finanzagentur, Agence France Trésor, MEF/Banca d’Italia, Tesoro Público, DSTA, Belgian Debt Agency, OeBFA, Finnish State Treasury, NTMA, IGCP, PDMA); ESM, EFSF, EIB, CEB, EBRD financial reports; the AFME Government Bond Data Report Q4 2025; SIFMA’s US Fixed Income Securities Statistics; the ECB Data Portal (BSI dataset); S&P Global Ratings, “Default, Transition, and Recovery: 2024 Annual Global Sovereign Default and Rating Transition Study”; rating actions verified against issuer investor-relations pages and the Wikipedia List of countries by credit rating. Lane and Rehn speeches as referenced. Author’s calculations throughout.

In December 2025 the European Central Bank announced that its 2026 thematic stress test would be a reverse stress test, conducted on 110 directly supervised banks and focused on geopolitical risk. Each bank will be asked to identify the scenarios that could produce a depletion of at least 300 basis points in its CET1 capital ratio. The exercise will use existing supervisory data templates, will inform and complement the SREP qualitatively in line with the broader 2026 ICAAP, and is — in the press release’s own language — “not intended to have any implications for Pillar 2 Guidance,” meaning the exercise is structured as a discovery exercise rather than an input to binding capital constraints. Aggregate results are due in summer 2026.

Read narrowly, this is a thematic supervisory exercise on a particular risk driver. Read more broadly, it is the first ECB thematic exercise to use the reverse methodology for directly supervised significant institutions, and the announcement frames it explicitly as a complement to the 2025 EBA exercise — “which assumed a common scenario for all banks and led to differences in their capital depletion.” That sentence in the press release does substantive work: the supervisor is framing the new exercise as addressing something the common-scenario approach does not.

This piece sets out why I think that framing is right. The argument has three parts, none of which is original to me but which fit together more cleanly than they are usually presented. First, the empirical track record of EU-wide adverse scenarios is harder to defend than the institutional discussion typically allows, even using the institutions’ own preferred severity metrics. Second, the methodological objection to single-scenario stress testing is mathematically tighter than the usual “models are imperfect” gloss suggests — and this matters, because the tighter version of the argument has a cleaner constructive response. Third, the methodological direction the ECB announcement points toward is more advanced than the announcement itself implies; the move has been compelling for at least a decade, supported by working papers from inside the major European supervisors, and is now consistent across European regulatory bodies.

The empirical record

Forward stress tests project an adverse scenario over a fixed horizon — typically three years — and ask what depletion of bank capital that scenario would produce. The scenario is published; the depletion is computed and reported; the supervisor and the public assess whether banks would have remained solvent. This is the structure of the EU-wide exercises since 2010 and of the US CCAR exercises over a similar period. The exercise has done useful work: disciplining bank capital planning, producing comparable bank-level data, standardising disclosures, and giving markets a coherent reference point for stress assessment. None of what follows is meant to question those benefits.

Whether the exercise has worked well as a representation of severe outcomes is a separate question. The most direct test is to compare scenario severity against what subsequently happened.

The chart is a heuristic comparison rather than a like-for-like forecast evaluation. Scenario severity and realised severity are measured over different windows — three-year cumulative paths against peak-to-trough declines — and scenarios are designed as plausible severe paths rather than as forecasts. With those qualifications, three observations from the data.

First, no adverse scenario in the series has projected a cumulative decline as severe as the realised peak-to-trough of either the global financial crisis or the COVID episode. The most recent 2025 scenario, calibrated against geopolitical risk and explicitly tightened relative to its 2023 predecessor, projects -6.3% cumulative real GDP — a more contained shock than what the EU economy actually delivered in either of the two major downturns of the last fifteen years.

Second, the 2020 contrast is the most direct. The ESRB scenario for the 2020 exercise was published on schedule in January 2020, projecting -4.3% cumulative real GDP over the 2020-2022 window. The exercise was cancelled in March 2020 as the pandemic arrived — the only time an EU-wide exercise has been cancelled mid-cycle. The realised peak-to-trough EU GDP decline between 2019Q4 and 2020Q2 was 13.3%. The scenario document itself, written weeks before lockdown, contained the line that its severity was “comparable to that observed in the global financial crisis from 2007 onwards.” The realised episode was substantially more severe by every reasonable measure of peak-to-trough decline, even allowing for the different time horizons of scenario and reality.

Third, the energy crisis cuts the other way. The 2023 stress test was calibrated against precisely the kind of geopolitical and energy-price shock that had begun to materialise — and projected -6.0% cumulative GDP. Realised EU GDP through 2022-2024 declined by approximately 0.2% peak-to-trough on the chain-linked volume series. The scenario was, on this metric, an order of magnitude more severe than the realised episode. Both directions of error are present in the same series.

A reader can fairly object that scenarios are not forecasts. The institutions are explicit on this point; the comparison to realised data is not a comparison of like with like. Accepted. But the methodological question remains: do single-point scenarios, however severe, capture the relevant range of outcomes? Realised shocks have repeatedly fallen outside the scenario envelope in both directions — which is exactly what we should expect if single-point scenarios are being used to represent events that have measure zero in a high-dimensional, nonlinear space.

A second observation, this time on the depletion side, sharpens the empirical case.

The 2025 EU-wide stress test results were widely reported as showing improved bank resilience, on the basis of a 109 basis point improvement in headline CET1 depletion relative to 2023 (both on a transitional basis). The decomposition tells a different story. Net earnings — predominantly net interest income — contributed +509 basis points to the capital ratio in 2025, up from +356 basis points in 2023. That tailwind is almost exactly what the elevated rate environment between the two cycles would produce. Credit losses, the line item that most directly measures realised risk, worsened by 32 basis points. Market and operational risk projections are not perfectly comparable across the two cycles, less because of a wholesale change in the stress-loss engines than because the 2025 exercise incorporated CRR3-related capital-framework changes, including REA restatements and output-floor effects. Even allowing for that, the headline improvement is overwhelmingly a rate-environment story rather than a risk story.

This is not a criticism of the EBA methodology; it is a feature of how single-scenario exercises decompose. Headline depletion measures the net of all driver lines and is sensitive to the environment as much as to the scenario. The decomposition is itself published, alongside the headline, in EBA results reports. But the headline number is what enters the public discussion, and a reader looking only at “-370bps vs -479bps” would draw conclusions about banking sector resilience that the underlying data do not directly support.

Both charts are facts about how single-scenario stress tests perform. Whether they should perform differently is a methodological question.

The methodological objection

The standard critique of stress tests is that “models are imperfect” or that “tail risks are hard to capture.” Both are true and both are weak. They invite the response that all empirical exercises have these problems and that stress tests are nonetheless useful — a response which is also true. The methodological case has to be tighter than this if it is going to do real argumentative work.

The tighter case has two layers, and they stack.

The first is a point about probability. A stress test scenario is a point in a continuous space — a several-thousand-dimensional vector specifying values for GDP and other macroeconomic variables across countries, sectors, asset classes, maturities, and quarters of the horizon. Any single point in such a space has probability zero under any continuous distribution. The exercise of asking “what is the loss under this scenario” is not the same as asking “what is a plausible severe loss.” It is asking what the loss would be at one arbitrary point. The severity of the point is itself ill-defined except as part of a region of points — which is what reverse stress testing, distributional approaches, and scenario sets are designed to characterise.

The second layer is about the loss function itself. Even granting that a scenario is “approximately right” in some informal sense, the loss function is not smooth in the relevant scenario parameters near regulatory thresholds and behavioural transitions. Outputs are not continuous in inputs near these transitions, and being approximately right on inputs can produce arbitrarily wrong outputs. This is what makes the first objection bite. If the loss function were smooth in scenario parameters, point estimates would be defensible as adequate local approximations. Because the loss function is not smooth, they are not.

The first objection holds in linear-Gaussian worlds. The second is what makes the first matter.

The dimensionality calculation is illustrative rather than literal. The variables in a stress test scenario are not independent and not uniformly distributed, so the volume-ratio formula does not apply directly, and the 33,600-variable count is an approximate multiplication derived from the scenario note rather than an official EBA figure. A quantitative analyst might fairly object that high correlation between variables reduces effective dimensionality to a handful of principal components — global growth, interest rates, inflation, perhaps a credit factor. Granted. But the non-smoothness of the loss function means that even slightly missing the right combination of those core factors can still produce entirely wrong outputs near the relevant cliff edges. Effective dimensionality buys you something for smooth functions and very little for non-smooth ones.

The non-smoothness objection is harder to wave at because it has empirical content. A direct example comes from a recent simulation framework for sterling money market funds.

Kumar’s framework approaches the problem from the right end: rather than assuming a particular adverse scenario and computing a fund’s response, it sweeps across the joint space of (redemption profile × market depth × WLA bucket) and computes failure probability as a surface. The headline finding is precisely that the redemption response has a kink at 40% WLA, with the cliff incentive structure activated as WLA falls toward the 30% regulatory minimum. The minimum itself is the supervisory threshold that triggers the acceleration; the 40% activation point is where the acceleration actually begins, ten percentage points before the minimum is hit. A stress test that linearises around current WLA values cannot represent either feature. The supervisor that wishes to know how much capital a fund needs against this risk is not well-served by a single scenario, however severe.

What makes Kumar’s contribution interesting beyond its specific NBFI application is that it is methodologically the same move as reverse stress testing for banks. Specify the failure condition; sweep the parameter space; identify the regions where failure becomes probable. The forward question — “is the fund OK under this scenario” — has been replaced by the reverse question: “what region of plausible futures threatens the fund.”

The constructive response

A useful clarification before going further. Three different exercises share the name “stress testing” and are easy to conflate. Supervisory stress testing is the common-scenario exercise applied bank by bank by the supervisor, asking how each institution would fare under a specified adverse scenario; results are used for comparability, oversight, and supervisory review. ICAAP reverse stress testing starts from a pre-defined failure or near-failure outcome and asks which firm-specific scenarios would bring the bank to that point; it is an internal capital-planning tool tied to the institution’s own vulnerabilities and business model, and has been required of banks under European supervisory guidelines for over a decade. Macroprudential distributional stress testing studies the distribution of losses, capital depletion, or credit supply across banks or the financial system; the question is not whether one bank survives one scenario, but how stress propagates across the system and what that implies for buffer-setting and financial stability.

The 2026 ECB exercise is the first thematic supervisory exercise to use the reverse methodology for directly supervised significant institutions — bringing together the structure of supervisory stress testing with a tool that has been in use for ICAAP purposes for some time. Worth noting that reverse stress testing is not the same as worst-case stress testing: it characterises the region of scenarios that produce a target loss, not a single extremal point. The shift is from one point to a set, not from one severe point to a more severe one.

Reverse stress testing has older roots. Banks have been required to conduct internal reverse stress tests as part of capital planning under various European supervisory regimes since 2010. The methodological argument for adopting it as the headline supervisory exercise — rather than as a complementary internal practice — has been articulated for at least as long. Borio, Drehmann and Tsatsaronis put the case cleanly in 2012, in a BIS working paper that has aged well: stress tests in their then-current form were “ill-suited as early warning devices” because the very structure of the exercise — point estimate from a model fitted to non-crisis data — could not capture the nonlinear dynamics that characterise actual financial instability. Their preferred response was not to abandon stress testing but to redesign it: more attention to the structural properties of the loss function, less reliance on the severity of any single calibrated point.

A more recent ECB working paper makes a structurally similar argument from inside the institution. Aikman, Angotti and Budnik (May 2024), in a paper titled “Stress testing with multiple scenarios: a tale on tails and reverse stress scenarios,” frame the case in language that is recognisably consistent with the earlier critique: scenarios “may not always be realistic or severe… can leave aside dangerous possibilities and create an illusion of safety.” The paper’s recommendation — multi-scenario analysis rather than single-point exercises, with reverse scenarios as a complement — sits comfortably alongside the move toward the 2026 exercise as part of the same methodological direction.

I find both of these arguments compelling. The constructive position they share is the right one. Forward and reverse stress testing are not substitutes; they are complements that answer different questions. The forward exercise has done useful work disciplining bank capital planning, producing comparable bank-level data, and giving markets a coherent reference point. The reverse exercise asks a different question — what region of the future threatens us — that the forward exercise structurally cannot answer. A supervisor that runs both is doing more work than one that runs either alone, and the press release’s framing of the 2026 exercise as a complement to the 2025 EBA exercise is exactly the right institutional posture.

There is one aspect of the methodological direction that is worth being honest about. The reverse exercise, like the forward exercise, requires a model. Sweeping the scenario space to characterise the loss frontier is computationally expensive and statistically demanding, and the regions it identifies are themselves model-dependent. The methodological objections that apply to forward stress testing apply, in a different form, to reverse stress testing too. The improvement is real but not unbounded; the loss function we are characterising is still being characterised by a model, and that model is still imperfect.

What reverse stress testing buys is not certainty about the future but a more honest representation of what supervisory analysis can and cannot do. Specifying a loss frontier and asking what plausible futures cross it is dimensionally honest in a way that specifying a point and computing the loss at it is not.

A regime change, slowly then suddenly

The argument I have set out here is not new. It was articulated in the academic literature by 2012, has been endorsed in working papers from inside the major European supervisors over the past two years, and is now being implemented in the form of a supervisory exercise. The interesting question is not whether the methodological objection is correct — it has been, by now, difficult to dismiss for some time — but why the institutional response has taken the shape it has and on the timeline it has.

My best guess is that two things had to happen at once. First, the empirical track record had to accumulate enough mismatches that the methodological objection could no longer be treated as a theoretical concern. The 2020 cancellation, the 2021 “most severe ever” exercise being followed by a year of NBFI stress that the scenario did not capture, and the 2023-2025 sequence of headline-level depletion improvements driven by rate environment rather than risk — these all happened in close succession and made the case empirically rather than methodologically. Second, the technical infrastructure had to mature enough that the alternative was operationally feasible. Reverse stress testing of the kind the ECB has announced, and parameter-space sweeps of the kind Kumar implements, depend on simulation frameworks, bank-level data infrastructure, and computational resources that were not realistically available a decade ago. The operational lift is substantial: the 110 banks in the ECB exercise have to construct loss surfaces rather than evaluate point losses, and that capability is genuinely new at supervisory scale.

Both conditions are now met. The 2026 exercise will not by itself replace the forward stress test apparatus; the press release is explicit that the reverse exercise complements rather than replaces the EBA’s common-scenario exercises. But it represents a meaningful change in the direction of methodological emphasis, and it is consistent with where the field — academic and supervisory — has been moving for some time.

The regime change has been slow. It seems to be becoming sudden.

Paweł Fiedor — The Macro Prudential View

Charts compiled from ESRB scenario notes for the 2014–2025 EU-wide stress test exercises, Eurostat quarterly GDP series namq_10_gdp (EU27, chain-linked volumes, seasonally and calendar adjusted), EBA 2023 EU-wide stress test results and EBA 2025 EU-wide stress test results. Cumulative growth from starting point taken directly from each ESRB scenario note where reported, or computed from annual adverse-scenario growth rates where the cumulative figure was not given in tabular form. Full referenced papers: Borio, Drehmann and Tsatsaronis, Stress-testing macro stress testing: does it live up to expectations? (BIS WP 369, January 2012); Aikman, Angotti and Budnik, Stress testing with multiple scenarios: a tale on tails and reverse stress scenarios (ECB WP 2941, May 2024); Kumar, A simulation framework for sterling money market funds (BoE WP 1177, March 2026). ECB announcement of the 2026 reverse stress test exercise: press release of 12 December 2025.

On 5 March 2025, the German 10-year Bund yield rose by 30 basis points in a single trading session — the largest one-day move since the fall of the Berlin Wall. The immediate trigger was the coalition parties’ agreement to suspend the debt brake and establish a €500bn infrastructure and defence special fund. But the magnitude of the move revealed something more structural: a market in which the most reliable buyer has been systematically withdrawing for two years, and in which the new buyers are not equivalent replacements.

This article examines that structural shift through four data series. It is not, at its core, a story about German fiscal policy, although that is the most visible current catalyst. It is a story about who absorbs European sovereign debt when the ECB does not — and whether those buyers are stable enough to do so without periodic crises of the kind 5 March 2025 briefly resembled.

The timing is not accidental. The Group of Thirty released its working group report on nonbank financial intermediation in April 2026, co-chaired by Agustín Carstens and Klaas Knot, titled Nonbank Financial Intermediation and Financial Stability: A Perfect Storm in the Making? The report’s central concern — that NBFIs have taken on a growing share of sovereign financing precisely as their structural vulnerabilities are increasing — maps directly onto what European sovereign bond data now shows.

Yields and their volatility

The yield chart tells a familiar story at first glance: rates rose sharply from near-zero as the ECB tightened in 2022, then stabilised through 2023–2024, with the five major euro area sovereign curves trading in a broadly correlated band. Bund–BTP spreads, which peaked at around 250 basis points in mid-2022, compressed to roughly 115 basis points by early 2025 — itself a notable fact given ongoing pressure on Italian fiscal metrics.

What is less visible in yield levels is volatility. The rolling realised volatility chart below makes it explicit.

The 2022 spike is expected — the ECB moved faster than at any point in its history, and markets were repricing duration risk across the entire curve simultaneously. What is more interesting is what happened in 2025. The March spike briefly exceeded the 2022 peak in short-term volatility terms, and it occurred in a regime that had looked, by the surface metrics of 2024, relatively calm.

The April episode — triggered by US tariff announcements that sparked a global risk-off rotation, initially driving capital toward core European sovereigns even as it unsettled peripheral spreads — produced a secondary spike. J.P Morgan & ESMA data (via ESRB report) showed that during the episode, European high-yield bond ETFs saw outflows of 6.4% of NAV in a single week, while sovereign bond funds saw simultaneous inflows — the flight-to-safety dynamic within the NBFI sector made visible, illustrating exactly the leveraged, fast-unwinding demand the G30 report warns about.

Two features of this overall pattern deserve attention. First, the 2025 spikes are idiosyncratic rather than systemic in origin — one driven by domestic fiscal news, one by US trade policy — suggesting the market has become sensitive to individual triggers in a way it was not when the ECB was a reliable marginal buyer.

Second, neither episode produced lasting dislocation. The ECB did not intervene. Markets self-corrected. This is the outcome policymakers point to as evidence that the absorption transition is proceeding smoothly. It may be the right conclusion — or it may reflect conditions that have not yet been genuinely tested.

The supply gap

The ECB’s withdrawal from European sovereign bond markets is neither subtle nor ambiguous in the data. Under the PSPP, the ECB built cumulative holdings of roughly €670bn in German sovereign debt, €540bn in French, €450bn in Italian and €320bn in Spanish bonds at their respective peaks. Since active portfolio reduction began in March 2023, those holdings have fallen by €202bn, €153bn, €149bn and €79bn respectively — a combined withdrawal of roughly €600bn across the five largest euro area economies in under three years.

The pace matters as much as the magnitude. The ECB is no longer reinvesting the principal payments from maturing securities under the PSPP; it is allowing its portfolio to run off at a measured and predictable pace — a portfolio that became, during the QE years, one of the largest single holders of European sovereign debt. The buyers on the other side of this withdrawal are heterogeneous — domestic banks, foreign official sector, asset managers, pension funds, insurance corporations, and an increasingly significant segment of hedge funds operating through the repo market. The ESRB’s NBFI Risk Monitor documents hedge funds’ average net borrowing in EU sovereign repo at €115bn in Q4 2024. That is not a trivial position. The pattern is not unique to the euro area. The Bank of England's Deputy Governor for Financial Stability noted on 17 April 2026 that net gilt repo positioning among hedge funds reached its highest level since data collection began in 2017 by early 2026, with borrowing concentrated among a relatively small number of firms pursuing similar strategies — a concentration risk that maps directly onto the European data.

What is striking about this transition is its coincidence with rising supply. Germany’s debt brake suspension and the €500bn special fund represent a structural shift in sovereign issuance that will persist for the better part of a decade. France, Italy and Spain face their own fiscal pressures. The G30 report notes that sovereign debt in advanced economies has expanded roughly 60% faster than credit to the private sector over the past fifteen years, and that NBFIs must increasingly serve as the marginal buyer as central banks withdraw. The European data confirms this is happening not as a projection but as a present reality.

The scissors effect

The fourth chart makes the supply-demand shift most concrete. In 2020 and 2021, the ECB absorbed roughly €52–55bn annually in German sovereign debt — covering between 25% and 40% of Germany’s net new borrowing in those years. The pandemic fiscal response was, in this sense, substantially ECB-financed. From 2023, the relationship inverted. The ECB withdrew €51.7bn net in 2023, a year in which Germany itself only net-borrowed €27.2bn. In 2024, ECB withdrawal (€72.2bn) was more than twice Germany’s net issuance (€33.3bn).

This is the scissors effect: simultaneously rising supply and withdrawing central bank support, meeting at a point where the residual buyer must absorb both the new issuance and the ongoing redemptions from the ECB’s portfolio. With German net borrowing rising again in 2025 (€67bn) and the special fund adding further issuance pressure from 2026, the structural demand for non-ECB buyers of German paper is growing in both directions at once.

The BlackRock Investment Institute, writing on 13 April 2026, concluded that increased German bond issuance “is already largely reflected in the current level of 10-year yields.” That may well be correct. But markets have a habit of interpreting the absence of stress as proof of resilience — precisely the behavioural bias the G30 report cautions against.

Who the new buyers are, and why it matters

The G30 report’s taxonomy of NBFI forms is useful here. The buyers filling the ECB’s role in European sovereign markets are not homogenous. Some — pension funds, insurance corporations, sovereign wealth funds — are genuinely long-horizon, buy-and-hold investors whose presence in the sovereign market is structurally stabilising. The FSB’s latest global monitoring report confirms that these investors have increased their sovereign debt holdings meaningfully, though gradually.

Others are not. The ESRB’s data on hedge fund sovereign repo exposure, and the G30’s documentation of near-zero repo haircuts for the largest hedge-fund borrowers — in some cases 50 basis points or lower — implying leverage ratios that can reach 200 times or more — point to a significant component of sovereign market demand that is highly leveraged, short-duration funded, and prone to rapid unwinding. The basis trade, in which hedge funds hold sovereign bonds financed through repo while taking offsetting derivatives positions, has become a meaningful source of demand in European sovereign markets. The April 2025 episode illustrated what the European equivalent could look like at larger scale under less benign conditions.

Critically, this is not a risk contained within the NBFI sector. The G30 report’s “transformation form” argument makes clear that while credit risk has migrated from banks to NBFIs, much of the associated liquidity risk remains concentrated in the banking system. When a leveraged basis trade unwinds, the prime brokerage banks are directly in the line of fire — which is why the G30 treats this not as a shadow banking problem but as a core financial system problem.

The FSB documents that NBFIs increased their share of advanced economy sovereign bond holdings by approximately 7.9 percentage points between 2021 and 2024. What this means in practice is that the marginal price-setter in European sovereign markets has changed — from a central bank with an unlimited balance sheet, no leverage constraint, and no redemption risk, to a collection of entities with varying degrees of leverage, short-term funding, and sensitivity to global risk appetite.

This does not make European sovereign markets unstable. Most of the time, the new buyer composition functions adequately. The 2025 episodes suggest that under episodic stress, the transition from central bank to NBFI as marginal buyer is visible in volatility even when it does not produce lasting dislocation.

The honest uncertainty is whether episodes that resolve without intervention are evidence of resilience, or of good fortune.

The regulatory gap

One dimension of this transition that the G30 report addresses directly, and that the European data makes urgent, is the absence of a central bank liquidity facility for NBFIs in the euro area. The Bank of England adopted its Contingent Non-Bank Financial Institution Repo Facility in 2025 — a pre-designed, contingent mechanism through which the BoE can provide repo liquidity directly to insurance corporations and pension funds under defined stress conditions, at penalty rates and with strict eligibility criteria. The facility is not standing; it activates on defined triggers. But its existence means the BoE has a documented, ex-ante response to NBFI liquidity stress in gilt markets.

The ECB has no equivalent. EUREP — the ECB’s repo facility for non-euro area central banks — is not designed for this purpose. The ECB’s operational toolkit for managing sovereign market dysfunction runs through bank intermediation and, ultimately, asset purchase programmes.

The G30 report is explicit: relying on broad asset-purchase programmes as the default backstop for NBFI stress creates moral hazard and blurs monetary-policy communication. No equivalent targeted, pre-committed tool currently exists in the euro area. This is not an argument for the ECB to backstop hedge funds. The G30’s framework carefully distinguishes between providing contingent liquidity to systemically important NBFI activities — pension funds, insurance corporations, large asset managers — under strict conditions, and open-ended support for leveraged trading strategies. The former has a legitimate financial stability rationale. The latter does not. The challenge is that designing a facility which credibly separates the two, in advance, is genuinely difficult — as the BoE’s CNRF design process illustrated. The difficulty of the design problem is, in the G30’s assessment, not a sufficient reason to avoid attempting it.

What to watch

The immediate catalyst for this article — the March 2025 Bund spike and its connection to German fiscal expansion — will fade as a market focus. German issuance will be absorbed, spreads will stabilise, and the volatility charts will normalise. That is almost certainly the right base case.

What will not normalise is the structural composition of who holds European sovereign debt. The ECB’s portfolio will continue to decline. German, French and Italian issuance will continue to rise. The NBFI share of the marginal buyer will grow further. And the institutional infrastructure for managing stress in that buyer base — data quality, supervisory frameworks, liquidity facilities, crisis simulation — remains incomplete by the most detailed practitioner assessment yet published on the subject.

The G30 report asks whether a perfect storm is in the making. The honest answer, consistent with the report itself, is that the conditions for one are assembling — and that the absence of a storm so far is not the same as the absence of risk.

Paweł Fiedor — The Macro Prudential View

Charts compiled from ECB Asset Purchase Programme statistics (April 2026), Bundesministerium der Finanzen (January 2026), ESRB NBFI Risk Monitor, and Investing.com. Full G30 report: Nonbank Financial Intermediation and Financial Stability: A Perfect Storm in the Making? BlackRock Investment Institute commentary (13 April 2026) linked in text.

Last week I used the IMF’s Global Financial Stability Report to make the case that ETF hoarding and passive flows were quietly reshaping emerging market debt dynamics. This week I am back at the same well. The GFSR, it turns out, has more to give — and the news cycle has helpfully provided a real-world stress test of one of its central anxieties.

The anxiety in question is stablecoins. Not the crypto-bro version of the argument — moon, lambos, number go up — but the macroprudential one. The IMF, the European Systemic Risk Board, and a handful of serious monetary economists have spent the past eighteen months constructing a framework for thinking about stablecoins as a financial stability problem. That framework now has a live case study: the Strait of Hormuz, where Iran’s Islamic Revolutionary Guard Corps has been collecting transit tolls from oil tankers in Bitcoin and USDT since mid-March 2026. Theory, meet practice.

Part I: What the IMF actually said

The April 2025 GFSR dedicated prominent analysis to crypto assets and stablecoins, and its tone was notably less hedged than the Fund’s usual register. The central concern is what the IMF calls “cryptoization” — the process by which residents of countries with weak or compromised monetary frameworks substitute dollar-pegged stablecoins for their domestic currency. This is dollarization by another name, but faster, cheaper, and harder to monitor. You do not need a US bank account to hold USDT. You need a smartphone.

The IMF’s concern is not symmetrical across countries. In advanced economies with deep financial markets and credible central banks, stablecoin adoption is largely a regulated integration story — a new payment rail sitting alongside existing infrastructure. The risk is different in economies with high inflation, volatile exchange rates, and weak institutional anchors. There, stablecoin adoption can quietly hollow out domestic monetary transmission, erode the central bank’s balance sheet, and accelerate capital flight in ways that are nearly invisible to conventional surveillance tools.

The countries named or implied in the GFSR — Argentina, Turkey, Nigeria, Lebanon, Venezuela — are not accidental. These are places where the dollar has long served as an informal unit of account and where stablecoin adoption is driven not by convenience but by survival. What is new is the scale and speed. The IMF’s July 2025 External Sector Report noted that stablecoin flows relative to GDP are most significant in Latin America and the Caribbean, and in Africa and the Middle East — precisely the regions with the greatest institutional vulnerability.

There is a second concern that sits at the opposite end of the risk spectrum but is equally striking. Stablecoins are not just a monetary sovereignty problem for fragile economies. They are becoming a structural feature of the US Treasury market.

Hélène Rey of the London Business School has argued that this dynamic amounts to the privatisation of global seigniorage — concentrating in a handful of private companies a function that central banks have exercised for centuries. The beneficiaries, she notes, are likely to be few given the strength of network externalities, with significant implications for the political economy of regulation.

Tether and USDC combined held approximately $146 billion in direct US Treasury securities at end-2025 (Tether's independently attested direct holdings were $122bn per its ISAE 3000R attestation, with Circle USDC comprising the remainder) — within $3.4 billion of Saudi Arabia’s holdings, and comfortably in the same league as Norway, India and Brazil. The IMF’s July 2025 External Sector Report flagged this directly, noting that at an earlier point in the year the two issuers collectively held more Treasuries than Saudi Arabia. The figure has since converged as Saudi Arabia’s holdings grew, but the point stands: two private companies, accountable to no central bank and subject to no formal reserve requirements under US law until the GENIUS Act passed in July 2025, had quietly become systemically relevant holders of the world’s benchmark safe asset. A confidence shock — a stablecoin run — would not stay in crypto markets. It would land in short-term Treasuries.

Part II: The ESRB and the multi-issuer loophole

European regulators have been watching a more specific structural vulnerability develop on their doorstep. The ESRB’s October 2025 report on crypto assets identified what it called the multi-issuer stablecoin problem, and issued a formal recommendation — ESRB/2025/9 — urging the European Commission to clarify that these schemes are not permissible under MiCAR.

The mechanics are worth understanding because they are the kind of thing that looks innocuous until it isn’t. A multi-issuer stablecoin involves an EU-regulated entity and a third-country entity — typically the parent company — co-issuing what is legally and technically a single, fungible token. The reserves backing the token are split across jurisdictions. Under MiCAR, the EU issuer is prohibited from charging redemption fees and must redeem at par, at any time. The third-country issuer faces no such constraint. In a stress scenario, non-EU token holders have a strong incentive to seek redemption through the EU entity — better terms, legally enforceable rights, a regulated counterparty. The EU issuer then faces redemption pressure it cannot fully hedge, from a reserve pool it cannot fully see, under a cross-border rebalancing mechanism that the ESRB explicitly describes as fragile.

Richard Portes of the London Business School, who co-chaired the ESRB’s Crypto Asset Task Force, has written up the academic case for urgency in a VoxEU column published in late 2025. His argument is direct: the multi-issuer loophole, if left unaddressed, exposes the EU financial system to contagion from crises originating in third-country jurisdictions, with EU supervisors holding responsibility for liabilities created entirely outside their remit.

The European Commission, as of writing, has not formally ruled the schemes impermissible. Several members of the European Parliament have written to Commissioner Albuquerque expressing concern. ECB President (and ESRB Chair) Lagarde has been more forthright in her public opposition. The institutional standoff is unresolved, which is part of what makes the ESRB recommendation significant — it is not an academic intervention but a formal macroprudential alarm from the body charged with systemic risk oversight in the EU.

Part III: The Strait of Hormuz — theory meets geopolitics

Which brings us to the news hook that makes all of the above feel less theoretical than it did a month ago.

Since mid-March 2026, Iran’s IRGC has been charging oil tankers up to $2 million per vessel to transit the Strait of Hormuz, accepting payment in Bitcoin, USDT, and Chinese yuan routed through Kunlun Bank outside SWIFT. Iran’s parliament formally codified the system in the “Strait of Hormuz Management Plan,” approved on 30–31 March 2026. At current traffic levels, public estimates from TRM Labs suggest the toll system could generate up to $20 million per day from oil tankers alone, with $600–800 million per month possible if LNG vessels are included.

This is the first time a state has deployed stablecoin infrastructure as a sovereign revenue mechanism at a major maritime chokepoint. It is not, however, a departure from Iran’s existing financial playbook. It is an extension of it. Chainalysis has documented IRGC-attributed on-chain activity growing from approximately $1 billion in 2023 to over $3 billion in 2025, based on OFAC designations and NBCTF seizure lists — figures that represent a lower bound, since they cover only identified wallets. The IRGC’s documented flows have overwhelmingly relied on stablecoins rather than Bitcoin, for reasons that are straightforward: stablecoins offer dollar-denominated value, high throughput, deep liquidity, and no issuer that can easily freeze an account.

That last point is important. In March 2026, Tether froze $6.7 million tied to IRGC and Houthi-linked networks. Bitcoin cannot be frozen by anyone. The choice of payment rail reflects operational learning about where the vulnerabilities in each system lie.

As this piece goes to press the situation is live and escalating. Iran declared the strait open on 17 April in line with a Lebanon ceasefire, then reversed course within 24 hours, reasserting “strict control” until the US lifts its naval blockade of Iranian ports. IRGC gunboats attacked a tanker on 18 April — no injuries, but a significant escalation. The ceasefire expires mid-week, with Pakistani-led mediation scrambling to extend it. What is not in flux is the underlying infrastructure: the toll system, the crypto payment rails, and the IRGC’s on-chain apparatus predate this crisis and will outlast any particular ceasefire. The Hormuz situation is the stress test — not the source of the vulnerability.

A brief note on epistemic caution: TRM Labs’ own Ari Redbord told Fortune that he was sceptical crypto was being used at scale for toll payments as opposed to being signalled as an available option. The situation was, in his words, “incredibly fast moving.” Subsequent on-chain reviews by Chainalysis (10 April) have reached the same conclusion. The Chainalysis framing is more bullish on the significance. Both are worth reading. What is not in dispute is that Iran has built the infrastructure for stablecoin-denominated state revenue collection and has been using it for sanctions evasion at scale for several years. The Hormuz toll system is the most visible deployment of that infrastructure, not its origin.

There is one political economy footnote that deserves a sentence. One commentator observed that if Iran were to demand payment specifically in USD1 — the stablecoin affiliated with the Trump family’s World Liberty Financial — the President of the United States would face a financial incentive to lift sanctions. The observation is not presented here as a prediction. It is presented as an illustration of how private stablecoin infrastructure can become entangled with geopolitical incentives in ways that conventional financial plumbing simply does not permit.

Part IV: Putting it together

The IMF, the ESRB, and Richard Portes have all been making versions of the same argument in measured institutional language: stablecoins are no longer a crypto-native curiosity. They are monetary infrastructure with systemic implications, and the regulatory frameworks governing them are running several years behind their actual footprint.

The framework they offer can be summarised across five interlocking risks. First, reserve concentration: if a major stablecoin issuer faces a confidence shock, the forced liquidation of its Treasury holdings could disrupt short-term funding markets well beyond crypto. Second, cryptoization: in fragile economies, dollar-pegged stablecoin adoption is quietly hollowing out domestic monetary sovereignty in ways that are hard to reverse. Third, regulatory arbitrage: the multi-issuer loophole is the EU-specific version of a global pattern in which jurisdictional gaps between stablecoin issuers create run risk and supervisory blind spots. Fourth, sanctions evasion: Iran has demonstrated that stablecoin infrastructure can function as a parallel financial system for a comprehensively sanctioned state, and the architecture is available to others. Fifth, dollar exorbitant privilege 2.0: the proliferation of dollar-backed stablecoins may reinforce rather than undermine dollar dominance, but it does so by privatising seigniorage — concentrating it in a handful of companies whose governance and accountability bear no resemblance to a central bank.

None of these risks is yet systemic in the sense that regulators use that word carefully. The IMF is explicit about this. Stablecoin market capitalisation remains small relative to global currency flows, and the transmission channels to traditional financial markets are still developing. But the pace of development — market cap roughly doubling in two years, IRGC volumes tripling, multi-issuer schemes securing MiCAR authorisation before the regulatory framework could catch up — is precisely the dynamic that macroprudential frameworks are designed to flag before the fact rather than respond to after.

The GENIUS Act in the US, MiCAR in Europe, and the ESRB’s recommendation are all attempts to close the gap. Whether the European Commission acts on the ESRB’s advice before the next stress test arrives is an open question. The Strait of Hormuz did not wait for an answer.

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Last month gave us a live demonstration of the mechanism this article is about.

When the Iran war began on February 28 (following US-Israeli strikes on Iran), foreign investors pulled $70.3 billion from emerging markets in a single month — the largest outflow since the pandemic rout of March 2020, according to IIF data reported by Reuters. The chart above shows what that looked like at the ETF level across three panels.

The top-left panel tells the price story. South Korea fell nearly 19% from its pre-war close to end of March. The broad EM index fell 9%. Brazil barely moved. The Korea vs Brazil contrast reflects something real about the shock itself — Asian tech manufacturing hubs are heavily dependent on Middle East oil imports, which makes them acutely vulnerable to an energy price spike. That is a genuine fundamental difference. But the speed, synchronicity and scale of the selling also reflected a market structure in which passive vehicles mechanically offload the same benchmark names at the same time. Every broad EM ETF holds the same Korea overweight. When the exit began, it was simultaneous across thousands of funds sharing identical index weights. Bloomberg reported that INDA and EWT — both in the drawdown panel — suffered record monthly redemptions of $1.4 billion and $1.1 billion respectively in March, confirming that price declines were accompanied by large-scale AP (Authorised Participant) redemptions into the underlying markets.

The lower-left panel adds something the price chart cannot show: the redemption channel made visible. It tracks EEM (iShares MSCI Emerging Markets ETF) shares outstanding — green bars are AP share creations, red bars are redemptions into the underlying market. Two things stand out. First, the inflow staircase in January and February: 98 million new EEM shares were created in nine weeks as risk appetite surged, representing roughly $5.8 billion of pre-war positioning in a single ETF. Second, and more important: prices fell sharply from March 2 but AP redemptions did not begin until March 16 — a full two weeks later. Once they started, 41 million shares were redeemed in eight trading days. The secondary market absorbed the initial selling through price decline. The structural forced selling came later, in a concentrated burst.

This two-week lag matters analytically. It means the price chart understates the eventual selling pressure — by the time AP redemptions activated, prices had already fallen and liquidity had already thinned. The redemptions then hit a market that was weaker than it had been when the first wave of selling began. That sequencing is not random. It is a feature of how the passive vehicle structure transmits stress, and it is what the rest of this article is about.

The IMF’s April 2026 Global Financial Stability Report Chapter 2, published this week, puts granular numbers on this dynamic across 50 emerging markets over two decades. And my own research explains the micro-mechanism that makes passive herding especially dangerous in debt markets — where the same logic produces not a visible, continuous selloff but a quiet accumulation of latent fragility that breaks suddenly under stress.

What the IMF found

Drawing on holdings data covering roughly 4,000 mutual funds and 7,000 institutional investors across 50 emerging markets, GFSR Chapter 2 documents something we suspected but could not previously quantify at this granularity. Since the global financial crisis, cumulative nonresident portfolio flows into emerging markets have approached $4 trillion, driven overwhelmingly by the nonbank financial sector. The NBFI share of EM portfolio debt liabilities has roughly doubled to 80% over two decades.

Within that universe, sensitivity to global risk varies sharply by investor type. Hedge funds are the most reactive, but passive mutual funds and ETFs are the most sensitive segment within the investment fund category — more so than active mutual funds, more so than pension funds or insurers. When global risk appetite deteriorates by one standard deviation in the VIX, passive funds and ETFs reduce their emerging market holdings significantly more than active funds. They are also more likely to pass investor redemptions directly through to underlying asset markets, given their limited flexibility to use cash buffers to absorb outflows.

The macrofinancial consequences are substantial. Countries whose debt markets rely most heavily on the flightiest investor quintile — defined by the GFSR as the top quintile of nonresident investors by VIX sensitivity, mainly hedge funds and passive vehicles — face a 28–45% decline in new debt issuance during stress episodes, spread widening of 30–120 basis points, and a 6 percentage point increase in downside GDP risk over the following quarter. These effects are persistent, remaining negative for up to four quarters on average, and are amplified for sovereigns with high debt ratios and firms with elevated leverage.

Figure 2.8 of the report makes this hierarchy crystal clear across two panels. Panel 2 shows that within the nonbank universe, hedge funds and mutual funds pull back most sharply from emerging markets when the VIX rises — insurers and pension funds show no significant adjustment. Panel 3 drills into investment funds specifically: passive strategies and ETFs display the largest additional sensitivity relative to their comparison groups, while the distinction between institutional and retail investors is not significant. The two panels together trace the mechanism from the broad NBFI universe down to the specific vehicle type — and the teal bars in the right panel are where the passive herding machine sits.

The accessibility channel: why passive herding works the way it does

The GFSR identifies passive funds and ETFs as the flightiest segment but does not spell out why their mechanics produce such powerful, synchronised behaviour. That requires looking at how ETFs actually transmit information and shocks to the securities they hold — and this is where the findings differ, in an instructive way, between equity and debt markets.

In research with Petros Katsoulis using the complete regulatory dataset of Irish-domiciled ETFs (€424 billion in AUM, roughly two-thirds of all euro-area ETF assets), we showed that ETFs form strong information links with underlying equities but weak ones with underlying corporate debt. The mechanism is arbitrage. When an ETF trades at a premium to its net asset value, Authorised Participants buy the underlying securities, deliver them to the ETF, and sell the newly created shares — creating a tight, continuous information channel between ETF prices and the prices of the underlying assets. But this only works when the arbitrage is cheap and fast to execute.

Exchange-traded equities satisfy this condition. OTC-traded corporate bonds do not. Search costs, transaction costs, and the post-crisis retreat of dealer market-making in corporate bond markets mean that APs face significant barriers to arbitraging ETF prices against the underlying bonds. The information link is therefore loose.

It is worth acknowledging that this accessibility asymmetry has real benefits in normal times. Passive vehicles have genuinely democratised access to EM assets, and the migration of liquidity traders to the ETF wrapper actually reduces cash bond market volatility when conditions are calm. The problem is what happens when the redemption channel activates under stress — which is where the normal-times stability becomes a liability rather than an asset.

The three panels below show all three dimensions simultaneously. A one-standard-deviation increase in ETF flows raises daily equity returns by 69 basis points but moves debt securities by only 0.4 basis points — a ratio of more than 170 to one. ETF illiquidity propagates to equity bid-ask spreads at 0.8 basis points; it has no measurable effect on debt spreads. Higher ETF ownership increases equity volatility — consistent with intensified arbitrage activity — but decreases debt volatility, because investors migrate to the more accessible ETF wrapper rather than transacting in the underlying bonds. The centre panel captures the return sensitivity contrast most vividly; the right panel’s sign reversal on volatility — positive for equities, negative for debt — is the single most important empirical result for what follows.

The sign reversal is not a curiosity. It is the mechanism.

The paradox: why weak links make debt more fragile, not less

Here is where the IMF’s macro findings and the micro-level evidence appear to point in opposite directions — and where working through that tension produces the most important insight. The matrix below maps the two transmission channels across the two asset classes. The bottom-right cell is where the IMF’s findings live, and it is coloured differently from the others for a reason.

The answer to the apparent contradiction is that the two bodies of evidence are measuring entirely different channels. My paper captures the arbitrage-information channel. Because corporate bonds are hard to access, APs cannot efficiently arbitrage the ETF against the underlying, the information link is loose, and ETF demand shocks do not propagate strongly into bond prices. Liquidity-motivated investors migrate to the ETF wrapper rather than transacting in the cash market, which can actually reduce bond market volatility in normal times. This looks, from the outside, like stability.

The GFSR is measuring the redemption channel. When end investors redeem en masse from a passive EM debt ETF during a risk-off episode, APs must eventually sell the underlying bonds regardless of whether the information link is tight or loose. The weakness of the arbitrage mechanism does not prevent forced selling. It just means the selling arrives without prior price discovery — and lands on a cash market that has been structurally hollowed out by the very same liquidity migration that made the normal-times volatility so low.

This is the paradox the bottom-right cell of the matrix above captures: the dynamic that makes ETF-to-debt information links weak under normal conditions leaves the cash market defenceless when the redemption channel activates under stress. Passive herding in equity markets is loud and visible in prices at all times. Passive herding in EM debt is quiet — and then catastrophic. The low normal-times volatility that the accessibility channel produces is not a sign of stability. It is the cliff being made steeper.

Note also what March 2026 showed about debt vs equity. The IIF data recorded $56 billion in equity outflows — the largest in at least 20 years — but only $14 billion in debt outflows. That asymmetry is consistent with the accessibility argument: the redemption channel hit equities first and hardest because arbitrage links are tight and price transmission is immediate. Debt markets absorbed less visible but still significant outflows, with the transmission mechanism working more slowly and less transparently. The GFSR’s spread widening and issuance data capture what that looks like at the macro level over a full stress cycle rather than a single month.

What the GFSR adds on scale and structure

Beyond the investor-type decomposition, the GFSR documents two structural features that amplify the mechanism above. The first is the scale of the shift itself. The two panels below show the growth of passive and active EM fund allocations since 2006 across both debt and equity. Read the two panels together and note that the right-hand axes are identical — making the gap between them meaningful rather than a charting artefact. In debt, passive share has risen from under 2% in 2007 to around 33% today. In equity the shift has gone further still, with passive now approaching half of all EM equity investment fund allocation. That near-parity in the equity panel is the most striking single fact in the chart and most readers will not know it.

The second structural feature is that the passive share gain is not simply a story of more money flowing in — it reflects active AUM actually shrinking in recent years while passive held up. The total height of the stacked areas in the debt panel peaked around 2021 and has not recovered to that level, but within that flat total the teal band keeps growing. Passive is not riding a rising tide. It is taking share from active in a mature and in some respects contracting market. That dynamic is what makes the redemption channel risk cumulative rather than episodic.

The GFSR documents a third amplifying feature: country-level buffers matter. Nonbank investors pull back significantly less from countries with stronger institutional quality, higher reserve adequacy, and lower public debt ratios. This creates a troubling asymmetry — the countries most dependent on flighty investors for external financing are typically those with the weakest buffers to absorb their sudden departure.

This is not an emerging markets story alone — even core sovereign borrowers are not immune. KfW — one of the world’s safest borrowers, a AAA-rated German development bank — issued a €5bn 10-year EUR benchmark in January 2026 and generated a €50bn order book. Trading-oriented accounts and hedge funds accounted for 54% of that order book, up from 41% two years earlier. Banks, traditionally the anchor buyers in SSA syndications, fell from 42% to 27% over the same period. KfW Treasury posted the investor breakdown on LinkedIn this week and it is worth looking at directly.

Two caveats are worth stating plainly. First, order book share is not the same as allocation — KfW notes that central banks and official institutions led actual allocations at 38%, and that hedge funds typically receive thin or zero allocations despite their outsized order presence. Second, KfW is not an emerging market. But that is precisely the point. The KfW data documents the growing dominance of short-horizon, trading-oriented accounts in the price discovery process for even the safest fixed income instrument in Europe. These accounts are setting the clearing price on a €50bn book. The passivisation and financialisation of the marginal buyer is not a vulnerability confined to fragile EM borrowers — it has reached the core of the global fixed income market. Scale that dynamic to EM debt, remove the central bank backstop, and add the redemption channel — and you have the mechanism the GFSR is now documenting at macrofinancial scale.

Policy implications

The GFSR’s policy recommendations are appropriate as far as they go: strengthen macroeconomic fundamentals, build reserve buffers, implement liquidity management tools for open-end funds, improve NBFI data reporting, and expand international cooperation on cross-border exposures. These are necessary conditions.

The accessibility channel points to several more targeted additions. Fund-level liquidity mismatch reporting should go beyond asset class labels to capture the accessibility of the underlying basket — specifically, how easily Authorised Participants can arbitrage ETF prices against the underlying securities. A bond ETF holding liquid investment grade credit is fundamentally different in redemption risk profile from one holding illiquid EM corporate debt, even though both appear as fixed income in current reporting frameworks. Swing pricing and anti-dilution levies should be calibrated to the accessibility of the underlying basket — the bar should be meaningfully higher for fixed-income ETFs holding illiquid EM corporate debt than for equity ETFs where the arbitrage cushion exists. Stress-testing scenarios at both fund and system level should incorporate the redemption channel explicitly, modelling the scenario where normal-times low volatility in cash bond markets coexists with latent, large-scale forced selling capacity in the ETF wrapper above it.

Most practically: supervisors and central banks in recipient countries should track the passive share and ETF ownership concentration of their debt markets as early-warning indicators. A rising passive share compresses normal-times volatility while fattening the left tail. That asymmetry is precisely what growth-at-risk frameworks should be capturing.

The bottom line

Passive investing is not the spark. It is an amplifier — and last month's EM selloff showed that amplifier working in real time. The IMF has now quantified how powerful it has become at systemic scale. The micro-evidence from ETF markets explains why benchmark-driven selling amplifies so asymmetrically across asset classes: accessibility governs whether ETF demand shocks create continuous, self-correcting transmission or accumulate quietly into a latent redemption cliff.

The contagion web is being rewired. Understanding its topology requires both the macro map the IMF has now provided and the micro-foundation the accessibility channel supplies. Policymakers and supervisors who treat passive flows as a second-order issue are working from yesterday’s map.

Paweł Fiedor — The Macroprudential View

There is a particular kind of financial confidence that deserves to be treated with suspicion. It is the confidence of those who design a system and then assure you, with impressive technical vocabulary, that the system cannot fail in precisely the way it is currently failing. Private credit has been producing this variety of assurance for several years now. The funds were semi-liquid, not illiquid. The caps were prudent, not restrictive. The ratings were rigorous, not captured. And the investors — overwhelmingly wealthy, sophisticated, advised — surely understood what they were getting into.

They did not, or they did and are now pretending otherwise. Either way, the exits are crowded.

I. The Mechanics of a Run

The chart below, sourced from Robert A. Stanger & Co. via the Wall Street Journal, tells the story with brutal economy. For most of 2022 through 2025, redemption requests from non-traded business development companies were manageable — a steady trickle of met withdrawals, small unmet amounts, nothing that disturbed the promotional material. Then in Q1 2026 the bars fall off a cliff.

What happened was not, despite what several asset managers have implied, a wave of irrational panic. It was rational behaviour, made inevitable by the structure of the funds themselves. To see why, consider a simple payoff table.

Imagine you are an investor in one of these funds. You have two choices: stay in, or request redemption. The fund has a 5% quarterly cap on withdrawals. Other investors face the same choice. The payoffs look something like this:

This is not a complicated game. The dominant strategy — the one that makes sense regardless of what others do — tilts toward redemption the moment you have any reason to doubt that everyone else will stay. And in early 2026, reasons to doubt were not in short supply. Loan defaults at First Brands and Tricolor. Blue Owl cancelling a fund merger. BlackRock TCP Capital reporting a 19% NAV write-down in a single quarter — having told investors just seven weeks earlier that its non-accrual ratio had improved. Once a few investors act on these signals, the logic becomes self-reinforcing. The run is not irrational. It is the Nash equilibrium.

Diamond and Dybvig described this mechanism for banks in 1983. The insight — that a solvent institution can be destroyed by a coordination failure among its creditors — earned a Nobel Prize in 2022. Private credit fund designers knew about Diamond-Dybvig. They believed quarterly caps and NAV pricing made their structures immune to it. What they underestimated was the first-mover advantage embedded in the cap itself: if only 5% can exit per quarter and you think 15% will try, the race to be in the first 5% is exactly the run they said couldn’t happen.

The data from four major funds in Q1 2026 illustrates how differently this played out depending on who blinked first.

Blackstone, running the largest fund, chose to protect its franchise at almost any cost — upsizing to 7% and injecting $400 million of firm and employee capital to meet 100% of requests. The optics required it; BCRED is too central to Blackstone’s retail strategy to be seen gating. Ares was more orthodox: it stuck to its 5% cap and pro-rated, leaving 57% of requests unmet. Blue Owl had two funds in the data. Its technology lending vehicle received requests totalling 40.7% of NAV — 5% paid out. Its marquee $20 billion direct lending fund, OCIC, saw requests reach 21.9% of fund value — again, 5% paid out. Across both vehicles combined, Blue Owl faced over $5.4 billion in redemption requests in a single quarter.

Public markets have already delivered their verdict. Blue Owl’s listed stock has fallen 61% over the past year, with the sharpest leg down beginning in January 2026 as redemption data began to emerge. There is a particular irony in the numbers: $OWL’s dividend yield has now risen to approximately 10% — higher than the distribution rate on its own non-traded BDC, OCIC, which pays around 8.9% to Class I investors. Those investors, locked in at the 5% quarterly cap, are earning less yield than they could obtain by buying the publicly traded manager at a distressed price in the open market. The illiquidity premium has not merely compressed. It has inverted.

II. The Banks Are in There Too, Somewhere

The direct redemption story is dramatic enough. But private credit does not exist in isolation. It sits inside a web of financing relationships that connects it, with varying degrees of visibility, to the banking system and beyond — as the diagram below shows.

The mechanism is straightforward. Funds like BCRED maintain enormous revolving credit facilities to manage deployment timing — BCRED alone disclosed $42.8 billion in committed debt capacity as of February 2026, drawn from over twenty banking relationships. These facilities are not passive. In a stress scenario, where portfolio companies draw on their own revolvers simultaneously, private credit funds may face sudden calls on liquidity from two directions at once: redeeming investors pulling from above, and borrowers drawing from below.

This is precisely the liquidity squeeze the IMF flagged in its April 2024 Global Financial Stability Report, which devoted an entire chapter to private credit. The report concluded, with the careful language of official bodies who do not wish to cause the crisis they are describing, that “liquidity risk could rise with the growth of retail funds.” It also noted that “multiple layers of leverage create interconnectedness concerns.” The full chain runs from bank revolvers to fund leverage to portfolio company debt to, ultimately, the retail investor who thought they were buying a slightly illiquid bond fund.

The portfolio overlap problem is harder to quantify but no less real. Private credit funds, competing for the same middle-market deals with similar underwriting standards, have inevitably accumulated correlated exposures. When First Brands went bankrupt, it was not a single fund’s problem. And the software sector — 21% of the Ares Strategic Income Fund’s portfolio, a similar proportion for many peers — represents a concentrated bet on AI-resilience that the market is now pricing with considerably more scepticism than it was a year ago.

The opacity runs deeper still, into the metrics that managers have been citing as evidence of portfolio health. Before examining the accounting, it is worth noting what the headline credit data already shows. According to Fitch Ratings, the default rate in its US private middle market portfolio reached 9.2% in 2025, up from 8.1% in 2024 — more than double the 4.5% default rate in the broadly syndicated loan market. Fitch notes that realised lender losses remained minimal, due to deferred payments and extended maturities. That caveat deserves scrutiny: deferred and extended is precisely the mechanism the non-accrual accounting exploits. Losses that have not yet been crystallised do not show up in the metrics managers show investors. The asset class that was sold as offering superior credit discipline has, at this point in the cycle, defaults running at twice the rate of the public market it was supposed to improve upon — and a reporting framework that is reasonably good at making them invisible until they are not.

And yet the fund-level metrics have not told this story clearly. The non-accrual ratio — the standard measure of loans in distress — is subject to a systematic distortion that makes it least reliable precisely when it matters most. When an impaired loan is restructured and written off, it exits the non-accrual count. The numerator shrinks. The percentage improves. Management issues a press release about progress.

This is what happened at BlackRock TCP Capital through most of 2025. Detailed analysis of the fund’s SEC filings — tracing every non-accrual loan back to its 2022 vintage — shows that more than half of the restructured positions ultimately ended in zero recovery. Not partial recovery. Zero. The non-accrual metric improved because the losses were being crystallised and removed from the denominator, while accounting reversals from those same restructurings generated unrealised “gains” that masked further deterioration. When Q4 2025 arrived with no restructurings left in the pipeline, the new markdowns hit NAV all at once.

This is not a TCPC-specific pathology. It is how BDC loan losses flow through financial statements — a feature of the accounting, not a bug introduced by any particular manager. The implication for investors reading fund reports is uncomfortable: a falling non-accrual ratio may be less a sign of recovery than a sign that the reckoning has already happened and is now invisible. To be fair to the managers: realized losses across the sector remain contained so far, and the bilateral nature of private credit relationships does allow for workouts and extensions that public bond markets cannot offer. The question is whether those workouts are resolving problems or deferring them — and on that question, the Fitch default data and the TCPC case study point in the same direction.

III. The Insurer in the Room

The Treasury meeting in April 2026 with domestic and international insurance regulators was not a courtesy call. It was an acknowledgement, carefully worded but unmistakable in its implications, that the private credit stress has a second act — one that runs through the balance sheets of American life insurers.

The connection has been building for a decade. Private credit, with its yield premium over public bonds and its apparent stability, was an almost irresistible proposition for life insurers seeking to match long-duration liabilities. The numbers confirm what the promotional material promised: private credit now accounts for roughly 46% of life insurer bond holdings, up from 29% a decade ago.

The concern is not simply the size of the exposure. It is the opacity. Life insurers have moved aggressively into private credit that is rated not by Moody’s or S&P, but by specialist private rating agencies whose methodologies are, in the Treasury’s delicate formulation, “called into question.” The NAIC has launched a study specifically into these securitised products. Several large insurers have moved substantial blocks of business to offshore reinsurers in Bermuda and the Cayman Islands, where regulatory standards are less demanding — a structure that makes consolidated risk assessment difficult even for those trying to perform it.

The particular risk here is not the same as the bank run. Life insurers are not facing redemption requests in any direct sense. But they are exposed to mark-to-market pressures if private credit valuations begin to reflect reality, to potential capital charges if rating agencies revisit their assessments, and to the generalised loss of confidence that tends to accompany the discovery that a large asset class was priced more optimistically than its fundamentals warranted. The feedback loop back to the funds themselves is worth noting: insurers facing valuation pressure or capital charges may reduce new allocations to private credit or, in stress scenarios, look to exit existing positions — adding to the redemption pressure at the fund level that started this story.

IV. Coming to a Continent Near You

Private credit is not an American story that Europeans can observe from a comfortable distance. The fundraising data makes this uncomfortable.

Europe’s share of private credit fundraising rose from 23% in 2024 to 33% in 2025 — a ten percentage point shift in a single year — while North America’s share fell from 72% to 63%, according to PitchBook’s 2025 Annual Global Private Market Fundraising Report. In absolute terms, European private debt fundraising hit a record $79.4 billion in 2025, up nearly 40% from the prior year. Much of this reflects a genuine structural shift: European companies have historically relied more heavily on bank financing than their American counterparts, and as European banks have retreated from leveraged lending under Basel III capital requirements, private credit has stepped into the gap. Two mega-funds — Ares Capital Europe VI (€17.1bn) and CVC European Direct Lending (€10.4bn) — helped push the numbers, but the trend predates them.

The regulatory architecture that might catch the problems is less developed. The ECB’s Financial Stability Review has flagged private credit risks with increasing urgency, but European insurance supervision remains fragmented across national authorities, and the Solvency II framework was not designed with the complexity of modern private credit structures in mind. The offshore reinsurance issue — Bermuda, Cayman — applies to European insurers too, perhaps more acutely given that several large European insurers have partnered with precisely the American private equity managers now at the centre of the US stress.

The pattern should be familiar to anyone who watched the 2008 crisis unfold. The instrument was invented in America, the risks were distributed globally, and the European discovery of the problem came with a lag that felt, in retrospect, embarrassingly preventable.

Private credit is not subprime. The borrowers are not buying houses they cannot afford; they are, mostly, established companies with genuine cash flows. But the structural parallel holds. This is an asset class that grew rapidly on the promise of higher returns and lower correlation. It was financed by retail and institutional capital that did not fully price the liquidity risk. It is now embedded in insurance balance sheets across two continents, and encountering its first serious test at a scale for which the architecture was not designed.

The architects, for their part, are confident the structure will hold. They were confident before, too. The more interesting question — the one Q2 and Q3 2026 will begin to answer — is what happens when the next round of NAV marks arrives, restructuring pipelines thin out, and quarterly redemption requests remain at levels the 5% cap was never designed to absorb. At that point, the difference between a liquidity stress and a solvency stress becomes less academic than it currently sounds.

The author writes on macroprudential and financial stability issues. Charts produced using data from Robert A. Stanger & Co., SEC EDGAR, Bloomberg, PitchBook, Milliman/S&P Global and the NAIC Capital Markets Bureau. The analysis of BlackRock TCP Capital’s non-accrual accounting draws on work by LeylaKuni, published at Accredited Investor Insights — strongly recommended. Blue Owl redemption data from SEC filings (April 2026); Fitch default rate from Fitch Ratings, “Private Credit Defaults & Recoveries 2025”, June 2026 (fitchratings.com).

Commissioner Maria Luís Albuquerque’s recent assurances regarding the state of Europe’s rather large (see below) Money Market Funds (MMFs) arrive wrapped in the frictionless vocabulary of Brussels diplomacy. We are told the European Union remains a premier destination for investors, that the 2018 regulatory framework has “worked well” in times of stress, and that the future requires merely “targeted clarifications” to ensure a “shared understanding” of appropriate liquidity levels.

One reads this with a certain intellectual vertigo. To assert that the current framework organically withstood the extreme market shocks of recent years is an exercise in profound historical revisionism. It is a fundamental misdiagnosis of the mechanics of systemic risk, and it demands a rigorous macroprudential rebuttal.

The Illusion of Intrinsic Resilience

To equate the survival of the short-term funding markets in March 2020 with the structural soundness is a dangerous category error. It mistakes the presence of a paramedic for the health of the patient.

During the onset of the pandemic’s ‘dash for cash’, corporate treasurers and institutional investors sought to liquidate their holdings with unprecedented velocity. This exposed the foundational fragility of the MMF model: the promise of daily, on-demand liquidity backed by portfolios of structurally illiquid, short-term corporate and sovereign debt. The sector did not independently survive this immense redemption pressure; it was rescued by the brute force of sovereign balance sheets.

The European Central Bank was forced to intervene via the Pandemic Emergency Purchase Programme (PEPP), actively buying commercial paper for the very first time to unfreeze the deeply impaired shadow-banking arteries. Simultaneously, the US Federal Reserve deployed the Money Market Mutual Fund Liquidity Facility (MMLF) to absorb toxic sell-offs, while the Bank of England activated the Covid Corporate Financing Facility (CCFF) to bypass the frozen short-term markets entirely. To conflate the survival of these markets via extraordinary sovereign intervention with the efficacy of the underlying regulation is a profound macroprudential misdiagnosis.

The Macroprudential Deficit and Institutional Non-Compliance

It is precisely this underlying architectural vulnerability that the European Systemic Risk Board (ESRB) sought to address in its 2021 recommendations. From a systemic risk perspective, the Low Volatility Net Asset Value (LVNAV) structure and its rigid regulatory thresholds actively incentivise a first-mover advantage, effectively guaranteeing a preemptive run during periods of acute stress.

Yet, as detailed in the damning February 2025 compliance report, the European Commission has been formally declared materially non-compliant with these vital directives. The Commission utterly failed to implement Recommendations A, B, and D, which called for the dismantling of these toxic threshold effects and a mandatory, tangible reduction in liquidity transformation.

Crucially, the Commission’s primary justification for inaction, that reopening primary legislation might impose compliance costs or temporarily alter the market’s commercial utility, was rightly dismissed as “unjustified” by the ESRB assessors. The ESRB handbook is unequivocally clear: systemic stability cannot, and must not, be held hostage to the short-term commercial convenience of the sector.

Global Divergence and the Fortress Balance Sheet

While the European Commission opts for the palliative care of non-binding guidance and supervisory convergence, the rest of the world is moving decisively to dismantle the structural threat.

The Financial Conduct Authority (FCA) in the United Kingdom, through its CP23/28 proposals, is demanding a radical recapitalisation of liquidity buffers. Refusing to rely on central bank backstops, the FCA is pursuing the complete statutory uncoupling of regulatory thresholds whilst pushing for an uncompromising minimum Weekly Liquid Assets (WLA) requirement of 50 per cent, and Daily Liquid Assets (DLA) of 15 per cent.

At the supranational level, the International Organization of Securities Commissions (IOSCO) has fundamentally revised its recommendations to enforce robust anti-dilution tools across the open-ended fund spectrum, shifting the cost of liquidity directly onto redeeming investors to extinguish the run incentive. The EU’s reluctance to enforce similarly rigorous structural mandates isolates it from the emerging international consensus.

The Geopolitics of Equivalence

This regulatory divergence is not merely an academic dispute; it is generating profound cross-border friction. Because of the FCA’s fortress balance sheet approach, HM Treasury has explicitly excluded EU MMFs from permanent equivalence under the newly operational Overseas Funding Regime.

Instead, to prevent a sudden, destabilising withdrawal of capital, the UK has been forced to repeatedly extend the Temporary Marketing Permissions Regime (TMPR) to the end of 2026, and the industry is clamouring for extensions into 2027, simply to avert a catastrophic cross-border cliff-edge for Sterling cash pools domiciled in Dublin and Luxembourg.

As demonstrated by the careful diplomatic language emerging from the Joint EU-UK Financial Regulatory Forum in London, the exchange of “observations on practices” regarding MMF resilience remains fraught.

A “shared understanding” of liquidity is undoubtedly an elegant phrase, but it will not suffice when the underlying financial architecture remains inherently unstable. MMFs perform a vital economic function, but they currently do so through the dangerous alchemy of liquidity transformation. Until we possess the structural courage to reform them at the legislative root, we are merely relying on the precarious hope that central banks will always be there to socialise the losses. True macroprudential resilience demands statutory iron, not semantic clarifications.

The AI ETF Boom and the Plumbing Beneath It

We are witnessing a historic reallocation of capital, and it is being executed through Exchange-Traded Funds (ETFs).

To understand the sheer scale of what is happening, you only need to look at the Nasdaq-100. Investors flock to the Invesco QQQ Trust under the assumption of diversified tech exposure. In reality, the fund has become incredibly top-heavy. As of early 2026, nearly 50% of the entire ETF’s weight is concentrated in just nine companies, almost all of them directly tethered to the artificial intelligence boom.

This concentration isn’t an accident; it is a reflection of a market that has violently bifurcated. The companies building the physical infrastructure for this new era have completely decoupled from the rest of the economy.

When we index the performance of these assets back to the end of 2020, the divergence is staggering. The VanEck Semiconductor ETF (SMH) has left both broad tech (QQQ) and small-cap equities (IWM) in the dust.

But perhaps the most telling metric isn’t past performance, it is current investor sentiment. Looking at year-to-date fund flows for 2026, we can see exactly how the market is placing its bets. Institutional and retail money alike are abandoning broad market exposure. QQQ has bled $10.7 billion in outflows, and small-caps have lost $4 billion. Meanwhile, capital continues to pour into the semiconductor space.

Investors are using ETFs as precision scalpels to slice into highly specific macro trends. They treat these vehicles as perfectly liquid, perfectly efficient conduits for their capital.

But this brings us to a critical, heavily overlooked problem: an ETF is not a magic wand that uniformly blesses its underlying assets with liquidity. It is a conduit. And like any conduit, what it transmits depends entirely on what it is connected to.

The Liquidity Illusion

There is a comforting, yet deeply flawed, tendency within the credentialed class to treat financial innovations as monoliths. When a new vehicle proves successful, we assign it a static set of characteristics and assume it will behave identically across all environments.

Nowhere is this intellectual complacency more evident than in our understanding of Exchange-Traded Funds (ETFs).

Over the past decade, ETFs have been heralded as the great democratizers of finance, granting investors immediate, continuous access to everything from highly liquid equities to notoriously opaque corporate bonds. The conventional wisdom dictates that ETFs inject liquidity into the system, acting as a stabilizing buffer. But this view suffers from a critical blind spot: it ignores the microstructure of the underlying markets.

An ETF is not a magic wand that uniformly blesses its underlying assets with liquidity. It is a conduit. And like any conduit, what it transmits depends entirely on what it is connected to.

This was the premise of the research I conducted with Petros Katsoulis at the Central Bank of Ireland, detailed in our paper, Information and liquidity linkages in ETFs and underlying markets. We sought to answer a specific question: Does the systemic footprint of an ETF change depending on the asset class it tracks?

The answer is a resounding yes.

The Arbitrage Engine and Market Accessibility

To understand the differential impact of ETFs, we must look at the mechanics of arbitrage. The price of an ETF share and the value of its underlying securities are kept in equilibrium by arbitrageurs who exploit price differences the moment they arise. This activity creates an “information link.”

However, this link requires accessibility.

When an ETF tracks equities, it tracks assets that are traded continuously on transparent, highly accessible exchanges. Arbitrageurs can move swiftly between the ETF and the underlying stocks. This hyper-accessibility forges a strong information link.

Corporate debt, by contrast, is a different beast. It is primarily traded over-the-counter (OTC) in private, bilateral transactions characterized by high search and transaction costs. It is fundamentally hard to access. Consequently, arbitrageurs are far less active, resulting in a weak information link between the ETF and the underlying bonds.

The Volatility Paradox

This divergence in market accessibility leads to starkly different systemic outcomes—some of which directly contradict the prevailing regulatory assumptions. Our analysis revealed three distinct phenomena:

1. The Contagion of Illiquidity: When an ETF experiences a liquidity shock (a sudden spike in trading costs), it propagates that shock directly to underlying equities. Because the information link is so strong, a disruption in the ETF instantly impairs the underlying stock. However, this illiquidity contagion does not spread to corporate debt securities. The weak information link acts as a firewall.

2. Asymmetric Returns: Demand shocks in the ETF market—represented by sudden inflows or outflows—affect the daily returns of underlying equities to a massive degree. Yet, these same ETF flows barely register on the daily returns of corporate bonds.

3. The Volatility Divergence: This is perhaps the most counterintuitive finding. What happens as ETF ownership of an asset class grows?

• In the equity market, higher ETF ownership actually increases the volatility of the underlying stocks. The ease of access supercharges arbitrage activity, making equity prices hyper-sensitive to ETF demand.

• In the corporate debt market, higher ETF ownership decreases the volatility of the underlying bonds. Because the underlying bonds are hard to trade, investors simply migrate to the ETF to satisfy their liquidity needs, leaving the underlying OTC market quiet.

The Policy Imperative

The illusion of uniform liquidity is a dangerous premise for both investors and financial regulation.

When we watch billions of dollars flee broad market tech (QQQ) and violently pivot into concentrated semiconductor bets (SMH), we aren’t just looking at a shift in market sentiment. We are watching a real-time stress test of the underlying market plumbing.

When regulators attempt to gauge the systemic risk posed by the multi-trillion-dollar ETF industry, they cannot rely on broad generalizations. The hyper-accessible equity markets underlying SMH and QQQ mean that these massive, sudden fund flows will inevitably breed arbitrage-driven volatility and potential illiquidity contagion in the underlying stocks.

However, if those same billions were flowing into high-yield corporate debt ETFs, the systemic footprint would be fundamentally different. In the corporate bond space, the risk is not contagion, but rather the hollowing out of the underlying market as liquidity migrates entirely to the ETF layer.

If we wish to build resilient macroprudential frameworks—and if investors want to truly understand the structural risks sitting inside their portfolios—we must stop looking at financial products in a vacuum. We must be willing to do the hard work of examining the plumbing.

In a highly interconnected world, one of the most persistent intellectual failings of the credentialed class, particularly within financial regulation, is the tendency to examine complex systems in isolation. We build elaborate, mathematically elegant models to stress-test banks, treating them as if they exist within a vacuum. But as the structural shifts of the past decade have shown us, the center of gravity in global finance has moved.

The conventional wisdom in macroprudential policy has long been to safeguard the banking sector. Yet, if we only look at banks, we suffer from our own form of institutional deafness. We fail to hear the signals emanating from the rapidly expanding non-bank financial intermediation (NBFI) sector, and specifically, investment funds.

What happens when an exogenous shock hits the system? Do banks and investment funds absorb the blow independently, or do their reactions feed off one another, creating a contagion web that amplifies the initial damage?

This was the core question my colleagues and I set out to answer in our recent paper, Shock amplification in an interconnected financial system of banks and investment funds, published in the Journal of Financial Stability.

The Conventional Wisdom: The Danger of the Silo

Historically, central banks and supervisory authorities have relied on single-sector stress testing models. We shock the banks. We see how the banks react. We declare the system safe or vulnerable.

But the reality of modern finance is deeply entangled. Banks and investment funds hold overlapping portfolios. Banks lend to funds; funds hold securities issued by banks. When a crisis strikes, such as the sudden economic halt caused by the COVID-19 outbreak, these entities do not merely absorb the shock in isolation. Their endogenous reactions, their desperate bids for liquidity and survival, collide.

The Contagion Web: Liquidity and Solvency

To understand this hidden plumbing, we built a novel model of contagion propagation using a remarkably granular dataset for the euro area. We subjected both sectors to a severe, multi-layered exogenous shock: a default shock, a market shock, and a redemption shock (where investors suddenly pull their capital from funds).

Our model revealed that the contagion mechanism operates through a dual channel of liquidity and solvency risk.

When investment funds face sudden, massive redemptions, they are forced to liquidate assets rapidly to generate cash. This phenomenon, the classic “fire sale,” depresses asset prices across the board. Because banks hold many of those exact same assets, their balance sheets instantly take a hit.

The findings are stark:

• Amplification, not containment: The combined, endogenous reaction of banks and investment funds significantly amplifies losses to the broader financial system compared to single-sector stress testing models.

• The Fire Sale Penalty: Adding the investment fund sector to our traditional banking model leads to substantial additional losses driven entirely by these endogenous market losses generated by investment funds’ asset liquidation.

• Capital Depletion: This interconnectedness causes a further depletion of banks’ capital ratios by around one full percentage point — a highly material impact during a severe systemic crisis.

The Policy Imperative

For those of us tasked with safeguarding the European financial system, the implications are clear. The days of siloed, single-sector stress testing must end.

If we continue to view the financial system as a collection of independent fortresses rather than a deeply integrated ecosystem, our models will remain elegant but dangerously incomplete. We must expand the scope of financial stability analysis to capture this institution-level contagion across different sectors.

Understanding the world requires us to map the connections others ignore. As the shadow banking sector continues to grow, our regulatory frameworks must evolve from monitoring isolated entities to managing the contagion web itself.

A recent Financial Times autopsy of the liberal order, titled “The pessimist who became a prophet,“ presents a dialogue between the commentator Martin Sandbu and the philosopher Michael Sandel. It is a fascinating, if somewhat suffocating, exercise in elite contrition. They dissect the failure of the technocratic consensus that has gripped the West since the fall of the Wall—a consensus that promised a flat world of frictionless commerce but delivered a fractured society of anxious debtors.

While their diagnosis of a “moral void” in governance is astute, the conversation inadvertently exposes the very solipsism that caused the rot. It reads like a seminar in the captain’s quarters of the Titanic, debating the hydrodynamic efficiency of the hull while the steerage passengers are already wading in freezing water.

Here is a reflection on that disconnect, structured through the lens of W.B. Yeats’ The Second Coming, a poem that feels uncomfortably like a morning news briefing.

Turning and turning in the widening gyre / The falcon cannot hear the falconer;

The central confession of the FT piece is that the “credentialed class”—the apparatchiks, the strategists, the Davoisie—constructed a world that functioned beautifully for themselves but severed all tether to the lived reality of the majority. Sandel rightly notes that by stripping decision-making of moral weight and subcontracting it to the “neutral” arbitration of market mechanisms, we created a vacuum.

But the metaphor of the gyre is more precise than they realize. The “falconer” (the leadership class) stands in the high tower of abstraction, shouting instructions about aggregate demand, ESG metrics, and long-term macroeconomic stability. The “falcon” (the voter, the saver, the citizen), meanwhile, has stopped listening. Not out of ignorance, nor a lack of education, but because the bird has realized, with a visceral clarity, that the falconer is no longer standing on the same earth.

The feedback loop hasn’t just broken; it was dismantled, wire by wire, by a leadership that preferred the sterile hum of their own models to the messy noise of the street.

Things fall apart; the centre cannot hold;

The article critiques the “managerial” style of governance—the conceit that if we simply pull the correct monetary levers, social cohesion will follow as a mathematical inevitability. This is the “idle voracity” of the modern state: the belief that printing money or drafting regulations can paper over the cracks of a hollowed-out culture.

In Europe, this tendency toward “misplaced deliberation” has mutated into an existential risk. As Mario Draghi’s recent report laid bare with a frankness bordering on brutality, the continent faces a “slow agony” unless it rediscovers the capacity for radical action. We have constructed a regulatory apparatus of baroque sophistication, perfecting the rules of a game that the rest of the world has stopped playing. While we deliberate endlessly on the harmonization of the internal market, our prosperity—the very engine of our social stability—stalls. The disconnect here is tragic: a political class that offers its citizens the world’s finest regulatory framework, while failing to deliver the economic dynamism required to pay for it.

Things fall apart when the Centre treats its own base not as constituents to be served, but as a stubborn variable to be managed. The Centre fails not because of external barbarians at the gate, but because it has hollowed out its own foundations, dismissing the legitimate, tangible anxieties of the majority as “misguided” or “provincial.”

Mere anarchy is loosed upon the world,

Sandel warns that a “moral void” invites chaos, framing the current populist backlash as the “anarchy” we must fear. This is a classic misreading of the timeline. The “anarchy” did not begin with the populist revolts. The anarchy was the deregulation of the social contract; it was the “creative destruction” that destroyed communities without creating anything in their place save for low-wage precarity and high-yield debt.

And what is the remedy proposed by our penitent elites? In the FT, Sandel suggests a return to “civic virtue” and “public discourse.” He pines for the days when citizens debated the common good in town halls. It is a charming, academic fantasy—the belief that the antidote to economic displacement is better conversation. It betrays a fundamental misunderstanding of the populist impulse. The working and middle classes are not revolting because they yearn for a Socratic dialogue on justice; they are revolting because the social contract has been breached. To offer “discourse” to a demographic that has seen its purchasing power evaporate and its cultural standing mocked is not a solution; it is an evasion.

The disruption we see now is not anarchy; it is a desperate attempt to re-impose order. It is the assertion of boundaries in a world that the elites insisted must remain borderless. When the leadership detaches policy from the values of the community, they dissolve the glue that binds the nation.

The best lack all conviction, while the worst / Are full of passionate intensity.

The tragedy of the current moment is the paralysis of the “best”—the well-meaning, educated establishment now wracked with guilt, holding seminars on “social cohesion” and writing op-eds about their own complicity. They are Hamlets in corporate boardrooms and parliaments, lacking the conviction to defend their own project because they suspect, deep down, that it was flawed from the start.

Meanwhile, the “worst”—the disruptors, the demagogues, the rude mechanicals—are winning because they possess “passionate intensity.” They offer clarity where the center offers caveats. They listen—or at least possess the theatrical genius to appear to listen—to the frustrations that the establishment has spent thirty years explaining away with charts.

Conclusion: Beyond the Slur

It is time to retire “populism” as a slur. It has become a lazy shorthand for “democracy that delivers results the elites dislike.”

We need not go as far as Alcuin of York’s warning to Charlemagne—Nec audiendi qui solent dicere, Vox populi, vox Dei. Alcuin, a true elitist, believed the riotousness of the crowd was “close to madness.”

But we have surely swung too far toward Alcuin’s patrician disdain. Somewhere between the “madness of the crowd” and the deafness of the technocrat lies the middle ground of functional leadership. It requires treating the voice of the majority not as divine truth, but certainly as a command that cannot be ignored. The falconer must come down from the tower, trudge through the mud, and learn to speak the language of the falcon again.