What’s Killing Productivity? Some Think It’s the Banks

LONDON—The birthplace of the industrial revolution is in dire need of innovation. Standing in the way: Britain’s mortgage-laden banks.

The U.K.—inventor of the factory system, steam engine and passenger rail—is at the forefront of a 21st-century global productivity slowdown. Growth in U.K. productivity, or output per hour worked, has halved since the financial crisis, leading some policy makers to call this era Britain’s lost decade. Among the world’s seven largest developed economies, only Italy has fared worse.

The causes are hotly debated, and include an ageing population, tighter regulation and the U.K.’s departure from the European Union. But a factor that has gained special attention: the way U.K. banks have tilted lending to the booming housing market.

Bank lending for projects that boost economic output, such as machinery and software, has stagnated. Research and regulators say the two trends are linked: As real-estate prices soared, banks shifted more capital toward housing, viewed as less risky because the loans were backed by tangible assets with rising values.

“The banking system is increasingly becoming a brake on the economy,” said Jonathan Haskel, a member of the Bank of England’s Monetary Policy Committee.

The U.K. is an extreme example of what’s happened in big economies around the world for the better part of this century. Central banks cut interest rates in the 2010s through early 2022 to make it cheaper for businesses to borrow and invest. But while debt rose sharply, most of it went toward real estate.

The world’s total assets—including those held by households, businesses and banks—more than tripled from 2000 to 2020, according to a report from the McKinsey Global Institute, a research group. Two-thirds are stored in real estate; only a fifth are in productivity-boosting assets such as factories, equipment and infrastructure, McKinsey said. “The historic link between the growth of net worth and the growth of GDP no longer holds,” the report said.

Among the world’s 10 biggest economies, the U.K. is tied with France for having the lowest share of net worth in assets that boost economic growth. Meanwhile, the U.K.’s home values and mortgage debt have exploded.

U.K. banks added £400 billion, equivalent to about $500 billion, to home lending in the decade through this February, Bank of England data show. Debt extended to businesses grew by only one-tenth of that amount.

The U.K.’s big banks “pulled back in the financial crisis and never really came back” in terms of business lending, said Richard Davies, a former regional head for Barclays’s U.K. business banking operations who now leads Allica Bank, a London startup that lends to small and midsize businesses. “The big banks are obsessed with residential mortgages.”

The obsession with mortgages leaves some businesses feeling sidelined.

Geometric Manufacturing, based in Tewkesbury, England, makes defence and cybersecurity products. Several years ago the firm asked a U.K. bank for a loan to design and manufacture a robotic arm to load its machines, an investment that would allow the factory to produce more with fewer workers, Managing Director Paul Wenham said.

Despite the option for a government guarantee through a U.K. program to help small businesses, the bank declined to participate, Wenham said. The company eventually received a small loan from a London-based startup lender. The loan came with a high interest rate and was smaller than what the company had sought.

His inability to get a bigger loan delayed the project by years, Wenham said. “We could have been reaping the rewards and benefits so much sooner,” Wenham said.

Dozens of startup lenders have stepped in to fill the void created by the retrenchment of big banks. They provided about half of all new loans to small and midsize businesses last year, government figures show. But they charge high interest rates on business loans, said Mike Conroy, director of commercial finance at UK Finance, the banking industry’s main trade group.

Conroy said the biggest factor behind weak business investment is a lack of demand, not supply. Many entrepreneurs are reluctant to take on debt, or simply don’t aspire to grow, he said. “The U.K. has many small businesses making a great contribution to the U.K. economy and local communities, even though they don’t aspire to be the next Microsoft or Google,” Conroy said.

Research in the U.S. and Australia shows that banks respond to rising home values by shifting capital away from businesses. U.S. banks located in areas with robust housing markets in the early 2000s bubble boosted mortgage lending while cutting business lending, according to a 2018 research paper in the Review of Financial Studies.

In the U.K., rules put in place after the financial crisis force banks to hold higher levels of capital for business loans, which are deemed riskier, than for mortgages.

Matt Hammerstein, CEO of Barclays’s U.K. operations, said banks have increasingly required all borrowers—whether homeowners or businesses—to put up physical assets that the lenders could sell if the borrowers fail to repay. Many business owners refuse to put up their assets, such as homes, as collateral and thus don’t win approval for loans, he said.

“What banks have done over time in order to be able to underpin their risk appetite is to expect entrepreneurs to put more of their own equity at risk,” Hammerstein said. “If you’re lending to a small business, particularly one that has intangible assets, you’re going to want some collateral.”

Default rates among established small and midsize businesses is low—about one in 50 will default in a given year, said Davies of Allica Bank. But determining each company’s risk—and thus what interest rate to charge and how much capital to hold—is less accurate and more time-consuming for big banks, which have instead shifted resources to mortgages.

In 2018, Jurga Zilinskiene wanted financing to develop software to expand her London-based language-translation business, Guildhawk. The 40-employee company translates documents for companies around the globe.

She asked a big U.K. bank for a seven-figure loan; they lent her a fraction of that, citing her lack of tangible assets that could back the loan if she defaulted. Many of her assets are intangible, such as intellectual property.

She worries that banks are too focused on making a quick profit rather than supporting the long-term health of the economy. “How can I compete with global enterprises in the United States, China?” she asks.

A sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.

The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.

The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.

The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.

This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.

The debt behind the AI build-out

Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.

Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.

JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.

The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.

That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.

A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.

When interest rates rise, those assumptions become less forgiving.

Inflation changes the calculation

September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.

The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.

CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.

Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.

Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.

The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.

China adds another source of pressure

Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.

Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.

The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.

That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.

A reset rather than the end of the boom

The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.

What has changed is the market’s willingness to overlook the price and financing structure of that growth.

The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.

More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.

For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.

Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.

The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.

Fact box

Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026

Philadelphia Semiconductor Index: Down approximately 11.4 per cent

Micron Technology: Down approximately 14.6 per cent

Samsung Electronics: Down approximately 18 per cent

SK Hynix: Down approximately 24 per cent

US September inflation: 3.7 per cent annually

Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion