Bank of England probes data-mining lending strategies fueling AI bets

The Bank of England is investigating the rise of financiers lending to data centers as a way to speculate on the future of AI, Bloomberg said.

The UK’s top bank has already been examining market risks that could arise if AI companies fail to meet lofty valuations, warning that many could come crashing down in a correction reminiscent of the dot-com bubble in the early 2000s.

Now, it is exploring the relationship between AI companies and financiers that are looking to place bets in the AI market, Bloomberg reported on Friday.

Although lending to data centers is still a niche market, it is poised to become a crucial source of funding, with an estimated $6.7 trillion needed by 2030 to keep up with the rising demand to power AI, McKinsey & Co said in April.

Source: Christophe Barraud

Bloomberg said the investigation was launched after BOE noticed an increasing amount of funds moved from hiring staff to spending billions of dollars on constructing data centers.

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UK crypto groups have also slammed the BOE’s proposal to limit individual stablecoin holdings to between 10,000 British pounds ($13,310) and 20,000 pounds ($26,620) — claiming it is not only restrictive but difficult and expensive to implement.

While the BOE said it wouldn’t impose those restrictions forever, UK banks have also imposed measures of their own, with about 40% of 2,000 surveyed crypto investors saying that their banks had either blocked or delayed a payment to a crypto provider.

BOE fears data center lending could trigger financial instability

However, the UK’s top bank holds the view that these emerging lending practices warrant close scrutiny due to their potential implications for financial stability.

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“If the projected scale of debt-financed AI and associated energy infrastructure investment materializes over this decade, financial stability risks are likely to grow,” it said on Friday.

“Banks would be exposed to this directly through their credit exposures to AI companies, as well as indirectly through their provision of loans and credit facilities to private credit funds and other financial institutions which are exposed to AI-impacted asset prices.”

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