From Bloomberg via Canada's Financial Post, October 24:
Data Center Lending Probed by BOE Amid AI Bubble Fears
The BOE has already called out the market risk from a surge in the valuations of firms in the industry, warning of the dangers of a sharp correction if “expectations around the impact of AI become less optimistic.”
Now, the central bank’s attention is moving to the links between AI companies and the financial sector, according to people with knowledge of the matter. Although lending is small at the moment, with much of the early construction works funded by equity, it’s expected to grow significantly. About $5.2 trillion of spending is required globally through 2030 to keep up with the demand for computing power for AI, according to McKinsey & Co.
One person said the BOE was looking into the area after growing concerned as the nascent sector’s spending migrated from hiring staff to spending billions of dollars on building and financing data centers with limited other uses.
“If the projected scale of debt-financed AI and associated energy infrastructure investment materializes over this decade, financial stability risks are likely to grow,” Bank of England staff wrote in a blog post 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.”
Indirect Exposure
One area of indirect exposure is through securitized loans for data centers, a second person said. There’s about $49 billion of data center asset backed- and commercial mortgage-backed securities outstanding, Bank of America Corp. estimated in August....
And at the Bank of England's Bank Overground site, October 24:
All chips in! Would a fall in AI-related asset valuations have financial stability consequences?
The purpose of Bank Overground is to share our internal analysis. Each bite-sized post summarises a piece of analysis that supported a policy or operational decision.
‘AI stocks’ comprise a growing share of the market capitalisation of US stock indices. These companies frequently trade at valuation multiples that imply high expected future earnings growth. These two facts have pushed some valuation multiples of US stock indices close to levels seen at the peak of the dot com bubble. While AI could have a transformational economic impact, which might justify these valuations, multiple factors make this outcome uncertain. Additionally, the physical infrastructure which underpins AI model training and inference is expected to require trillions of dollars of investment in the next five years, a significant share financed by debt. This blog sets out the potential financial stability consequences of a fall in AI-affected asset prices and how these are likely to grow in future.The capabilities of AI systems have continued to improve quickly in the last 18 months (Artificial Analysis (2025) Opens in a new window).
AI has the potential to have a transformational impact on many sectors of the economy as capabilities improve further (Crafts (2021) Opens in a new window). The potential impact of AI can already be observed. For example, the AlphaFold models developed by Google DeepMind have provided a breakthrough in predicting the 3D structure of proteins from their amino-acid sequences, solving a root-node problem that is now unlocking advances across diagnosis, protein engineering and drug discovery (Jumper et al (2021) Opens in a new window).....
....MUCH MORE