Blue Owl is one of Wall Street’s big names in private credit – a manager of nearly $300 billion in assets. The company’s logo is an owl: the animal that, according to legend, can see everything, even in the dark.

On February 19, 2026, Blue Owl restricted withdrawals from one of its retail-focused funds and quickly sold $1.4 billion in loans to raise liquidity. Investors who wanted out couldn’t get out. The stock has fallen nearly 60% over 13 months.

The blue owl in the coal mine had not seen it coming.

It reminds us of something we have seen before.

In the mid-2000s, many were warning about the American housing market. Lending standards were too loose. Too much capital was chasing too few good loans. And those bearing the risk often didn’t know they were doing so. We know how that story ended.

There is now a new part of the financial system that deserves the same attention. It is called private credit. Most people have never heard of it – and that is itself part of the problem.

Regulatory arbitrage and monetary policy created this market

Private credit is fundamentally a child of two policy choices.

The first was regulation. Banks were subjected to far stricter capital requirements via Basel III after 2008. The intention was understandable enough – but the consequence was predictable: capital and credit demand do not disappear because banks withdraw. They move precisely to where regulation does not follow.

Private credit funds operate without equivalent capital requirements, without the same transparency requirements, and without meaningful macroprudential oversight.

This is the definition of regulatory arbitrage – and it is a foreseeable consequence of asymmetric regulation, not an accidental side effect. The IMF noted in its Global Financial Stability Report in April 2024 that insurance companies were also incentivized to move into private credit precisely because the capital charges are lower and less risk-sensitive than those applicable to commercial banks. Regulation did not reduce risk. It relocated it.

The second was monetary policy – but let us be precise here. This is not the story of a decade of near-zero rates after 2008. That is the wrong diagnosis.

This is the story of what happened from 2020. The COVID response triggered the largest expansion of the American money supply in peacetime history. M2 grew by nearly 27% year-over-year in early 2021 – the highest peacetime rate since the Federal Reserve was founded in 1913. Some of this expansion was justified given the lockdowns. But it continued far too long.

That sent a tsunami of capital into private credit, because institutional investors desperately sought returns in a world where traditional fixed income products yielded nothing.

The market grew from $2 trillion to $3 trillion in precisely that period. When the money supply and rates finally turned from 2022, enormous sums were already locked into illiquid structures held by borrowers priced for a world of extraordinarily cheap money.

Regulation that does not eliminate risk, but merely displaces it – combined with a tsunami of liquidity. That is precisely the cocktail that mixed the subprime crisis.

The Austrian school element: the AI boom as malinvestment

It is worth drawing on an older analytical tradition here – but with an important caveat.

Friedrich Hayek and Ludwig von Mises were the two central figures of the Austrian school – a tradition in economic thinking that flourished in interwar Vienna before spreading to London and Chicago. Hayek received the Nobel Prize in Economics in 1974.

Their theory of the business cycle – known as Austrian Business Cycle Theory (ABCT) provides an explanation of what happens when central banks hold interest rates artificially low for too long.

The argument is simple. When the rate is lower than the market would have set itself, a false signal is sent to investors: capital is cheaper than it really is.

This attracts investment into projects that only look profitable at artificial financing costs – not at the natural rate. Hayek and Mises called this malinvestment – misallocations that look sensible during the boom, but are exposed brutally when monetary policy normalises.

But here is the caveat – and it is important. Austrian Business Cycle Theory is a theory of the unsustainable boom. It explains how the misallocations arise. It does not explain what happens next – and in particular, it does not tell us whether the bust will become a catastrophe. That depends on something else entirely: monetary policy.

The AI boom is a textbook example of the first part of that story.

What we could all ‘The Tesla boom’ of 2020-21 was to a large extent what financed the training of ChatGPT. The COVID liquidity injection sent capital into tech equities and pushed financing costs for AI companies below the natural rate – precisely the Hayekian mechanism, just with a modern transmission. Credit channels kept the expansion going far beyond what the underlying productivity numbers could justify.

Now we are in the middle of the massive buildout of data centres necessary to make the business models profitable – the four largest tech companies spent $360 billion on AI infrastructure in 2025 and are planning $650 billion in 2026. And the financing story is becoming increasingly speculative: AI companies are seeking capital in the Middle East, the Trump administration is talking about using Fannie Mae and Freddie Mac to finance the sector. It resembles the Icelandic banks in 2006-07, rolling around finding new liquidity sources while the warning lights were flashing.

The underlying problem is that the business model that must repay the debt is far weaker than assumed. Microsoft’s AI chief Mustafa Suleiman recently promised that AI would automate most office jobs within 12-18 months. A large study from the National Bureau of Economic Research of 6,000 senior executives shows that nearly 90% report AI has had no measurable effect on employment or productivity. Penn Wharton estimates AI’s contribution to productivity growth at 0.01 percentage points in 2025.

That is not an argument against AI as a technology in the long run – I am after all a huge fan of Large Language Models and a addictive user of LLMs – but it is an argument against pricing $650 billion in annual infrastructure investments on promises that the data consistently contradict.

Private credit and the AI boom are not two separate stories. They are two symptoms of the same misallocation of capital – both created by the same COVID fiscal and monetary expansion, both now under pressure as the bill is presented.

Moral hazard under the Trump boom

On top of regulatory arbitrage and the COVID monetary expansion came a third element: moral hazard on a grand scale.

I have for some time been warning about the dangerous fusion of the Trump administration and parts of American business – particularly the tech sector. When Trump administration AI czar David Sacks says “we can’t afford to go backwards”, I read it as an implicit promise: the government will underwrite the AI boom.

And when large tech companies are increasingly defined as strategically important – as “too big to fail” – there arises precisely the incentive problem that economist Robert Hetzel identified in his analysis of the financial crisis: financial institutions take greater risks when they know others bear the consequences. Gains are privatised. Losses are socialised.

This is not a new phenomenon. It is the same dynamic we saw with Fannie Mae and Freddie Mac before 2008. And it almost always ends the same way.

The cockroaches

The warning lights began flashing in earnest in the autumn of 2025. Let us go through the events in chronological order – because the pattern is more troubling than any individual episode in isolation.

Tricolor Holdings collapsed first. The company operated as both a used car dealer and a subprime lender – packaging high-yield car loans to credit-impaired borrowers into AAA-rated securities and selling them on to investors. When the repayments failed, the whole construction collapsed.

Fifth Third Bank is now accusing Tricolor of fraud, claiming the company pledged the same assets as collateral for multiple loans simultaneously. Investigators are reviewing what may prove to be a manipulated loan database.

First Brands Group followed shortly after. Just weeks before the bankruptcy, the company was marketed by Jefferies Investment Bank as an opportunity for $6 billion in lending – and the company was said to have nearly $1 billion in cash.

It collapsed anyway. It had borrowed massively for acquisitions, then borrowed again against invoices and inventory – and when tariff pressure hit imported components, there was no margin left. Jefferies, Millennium Management, JPMorgan, Barclays, and Fifth Third Bank are all exposed.

Jamie Dimon put it precisely: “When you see one cockroach, there are probably more.”

Then came a series of events that together sketch a pattern. BlackRock wrote down a private loan from full value to zero in three months. This is not as surprising as it sounds: private credit loans are not traded on markets but valued using internal models – what is known as mark-to-model. The IMF documented in its Global Financial Stability Report in 2024 that adjustments to private credit valuations are systematically smaller and slower than in public markets, and that it takes at least four quarters for prices to converge after a shock.

Losses are there before they are visible. A related warning sign is the sharp rise in payment-in-kind interest – where borrowers pay their interest by adding it to the loan principal rather than in cash. The IMF found that the payment-in-kind share in business development company portfolios doubled between 2019 and 2023. Borrowers are not defaulting. They are deferring. Blue Owl restricted withdrawals and sold assets to raise liquidity. Blackstone’s large private credit fund BCRED experienced redemption requests in early 2026 that exceeded the fund’s quarterly cap. And Morgan Stanley and Cliffwater have both been forced to limit withdrawals from their retail-focused funds after investors tried to redeem more than the structures allow.

The official default rate has risen steadily: from 1.76% in Q2 2025 to 1.84% in Q3 and 2.46% in Q4 2025 according to Proskauer’s Private Credit Default Index. That still sounds low – but when debt restructurings and creative loan extensions are included, the real rate approaches 5%.

Fitch puts the actual default rate in private credit at 5.8% through January 2026 – the highest since the index began. In February 2026 alone, 11 default events were recorded, nearly double the monthly average for all of 2025.

Mohamed El-Erian describes it as the “ATM scenario”: investors who cannot exit illiquid positions begin selling what they can sell – regardless of asset class. “If you can’t sell what you want, you sell what you can.”

That is the classic contagion mechanism – not losses, but liquidity pressure that propagates. It resembles a traditional bank run.

And lurking behind the share prices is a mechanism that has not yet fully played out.

The large private credit managers are today rated at the lower end of investment grade. One or two notches down, and they fall below the investment grade threshold – and this is not just a question of prestige. Pension funds, insurance companies, and large bond funds operate under mandates that forbid them from holding securities below investment grade.

A downgrade to junk triggers automatic forced selling from all these institutional investors – not because they want to, but because they are regulatorily obligated to. The IMF estimated in 2024 that pension funds and insurance companies globally had more than $600 billion invested in private credit funds – a figure that has grown rapidly since.

Some of the world’s largest pension funds, with combined assets exceeding $7 trillion, have significantly increased their allocation to private credit while simultaneously raising their financial leverage. The IMF identified this combination – illiquid assets and leveraged balance sheets – as a specific systemic risk. When collateral calls come, these institutions sell what is liquid. That is El-Erian’s ATM scenario in institutional form.

UBS estimates that in a severe AI disruption scenario, the US private credit default rate could hit 13% – twice the stress level for leveraged loans.

That creates precisely the cascade we know from 2008: forced selling pushes prices down, which pushes other funds toward the same threshold, and suddenly it is no longer just private credit under pressure, but all liquid assets that investors must sell to create room on the balance sheet. El-Erian’s ATM scenario, but in a rules-based and automated version.

The blue owl in the coal mine was not the only bird in the mine.

The near-perfect copy of 2008

One must be precise here. $3 trillion sounds like a lot, but in global financial context, the private credit market is relatively modest. The American equity market alone is about 15 times larger. The global bond market is more than 30 times larger.

But that is the wrong way to frame the question.

The subprime market was not the world economy’s largest market in 2006 either.

It still triggered the worst financial crisis since the 1930s. Then-Federal Reserve Chairman Ben Bernanke said himself in 2007 that the problems were “contained”.

They were not – because it was not about subprime’s absolute size, but about its connections to the rest of the financial system and what it revealed about the broader misallocation of capital. It is worth noting that the IMF’s own Global Financial Stability Report from April 2024 concluded that the financial stability risks from private credit “appear contained at present”. That is a precise echo of Bernanke’s formulation. It may prove equally accurate.

That is precisely the same point here. Private credit may not be large enough in itself to trigger a global crisis. But it can be the symptom of a far larger misallocation of capital – driven by the same COVID expansion, the same artificially low rates, and the same moral hazard – that will manifest as losses elsewhere in the financial system as reality catches up with the valuations made in a world that no longer exists.

This is where the data matters. U.S. nominal GDP growth remained relatively stable at around 5-6% through 2006 and into early 2007 – even as the first subprime warning signs appeared and global imbalances were becoming visible. The private credit market was wobbling. But the economy was not yet in crisis. It was only when those financial tensions translated into a de facto monetary contraction – and NGDP growth began to fall sharply through 2007-8 – that a financial correction became a macroeconomic catastrophe.

Critically, central banks made it worse. Spooked by what they perceived as bubble re-ignition – and facing rising headline inflation from an oil price surge – they turned hawkish at precisely the wrong moment (a number of central banks even hiked interest rates during the Summer of 2008). The result was a collapse in nominal spending that turned a necessary market correction into the Great Recession.

Secondary deflation, as Hayek called it, is not a natural consequence of a bust. It is a consequence of monetary policy failure.

The same risk exists today. Private credit may well be mis-priced. AI investment may well include substantial malinvestment. These corrections can be painful. But they do not have to become systemic crises. The key variable is not the size of the bust. It is whether the Fed ensures nominal stability through it.

On February 28, 2026, the US and Israel launched “Operation Epic Fury” – a coordinated strike on Iran that killed Ayatollah Ali Khamenei and threw the country into chaos.

Iran responded with drone and missile attacks on the Gulf states and effectively closed the Strait of Hormuz – the narrow passage through which 20% of the world’s oil consumption passes daily. Brent crude, which was trading below $70 per barrel at the start of February, hit above $100 earlier this week. That is a price increase of over 35% in fewer than four weeks.

Private credit is already cracking, as described above. The AI boom is under pressure from rising financing costs – and higher energy prices is not exactly good news for the energy intensive AI sector either. And now the oil price shock is a reality – the classic stagflation scenario that economists since 1973 have feared repeating.

In that situation, the Fed faces a near-impossible choice. The mandates point in opposite directions. Inflation is too high to ease.

The credit tightening calls for easing. This is the classic monetary policy dilemma that institutional rules and mandate structures make nearly impossible to resolve correctly – and it is precisely the dilemma that in 2008 turned a credit crisis into an economic catastrophe.

There is a way out of this dilemma – but it requires a framework the Fed does not have. A 4% NGDP level target would cut through the confusion between supply-side inflation and demand collapse.

Under such a framework, a central bank does not respond to rising oil prices by tightening – because oil price inflation does not represent excess nominal demand. It responds to falling nominal spending – which is the actual threat.

In 2007, the Fed had no such framework. It does not have one today either. As the German-American economist Rudi Dornbusch put it: “No postwar recovery has died in bed of old age – the Federal Reserve has murdered every one of them.”

And if Kevin Warsh – Trump’s candidate as the new Fed chairman –-is at the helm, it becomes even harder.

Warsh is ideologically sceptical of quantitative easing – the central bank’s purchases of bonds to pump liquidity into the economy when rates hit zero – and has historically viewed the Fed’s balance sheet expansion as a problem rather than a solution.

In the scenario where rates hit the zero lower bound and conventional monetary policy runs out of road, the political and ideological resistance to reaching for precisely this instrument will be maximal – at precisely the moment it is most needed.

Add to this a chaotic White House that is actively undermining the central bank’s credibility and institutional independence, and the picture is complete.

This is not a prediction. Most scenarios probably end with a gradual correction – losses at the weakest actors, tightening of standards, consolidation. That is the normal credit cycle.

But the pieces are placed in a way that is uncomfortably reminiscent of 2008. Only with a markedly worse political situation, a Fed chairman who is not Ben Bernanke, and a supply shock that Bernanke never had to contend with.