Circular AI financing deals echo 1980s savings-and-loan crisis risks
Quick Look
Interlocking financial commitments among AI companies like OpenAI, Nvidia, and Anthropic resemble pre-crisis savings-and-loan daisy chains, raising concerns that industry growth is being self-financed amid rising debt and systemic risk.
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Why It Matters
The article draws a parallel between current AI industry financing practices and the interconnected transactions that preceded the 1980s savings-and-loan crisis, where daisy-chain deals obscured risks and contributed to widespread bank failures.
It’s time to ask how much of the industry’s extraordinary growth is being financed by the same companies benefiting from it
James David Spellman, a graduate of Oxford University, is principal of Strategic Communications LLC, a consulting firm based in Washington, DC.
Published: 8:30pm, 7 Sep 2026Updated: 9:27pm, 7 Sep 2026
The “circular deals” among AI titans increasingly resemble the “daisy chains” of the 1980s savings-and-loan crisis.
Forty years ago, interconnected transactions obscured the dangers, multiplied systemic risks and helped inflate asset values before roughly a third of US thrift banks failed. Today’s financial engineering – an incestuous ecosystem of interlocking multi-year commitments to provide financing, buy semiconductors, secure gigawatts of power and lease data centres – could meet a similar fate, especially if revenue fails to outpace costs or a black swan event eviscerates artificial intelligence (AI) trajectories.
OpenAI has struck deals with Nvidia, CoreWeave and others ahead of an initial public offering planned for next year while competitors Anthropic and xAI have pursued similar agreements. Anthropic’s US$35 billion cloud-computing deal with provider Lambda is the latest example. Last month, the AI developer signed a US$45 billion arrangement with another Nvidia-backed neocloud, Nscale, to rent data-centre capacity.
Nvidia is involved in more than US$750 billion worth of AI investments, financing deals and partnerships, according to PitchBook. Demand from AI labs receiving Nvidia financial support will account for roughly a quarter of the company’s business next year, CFO Colette Kress said.
The rash of AI investments is unprecedented in scale – 4.5 times the level three years ago, according to Bank for International Settlements data. This raises a question: how much of the industry’s extraordinary growth is being financed by the same companies benefiting from it?
Meanwhile, hidden risks are colliding with a borrowing binge well under way. The five largest hyperscalers carry roughly US$1.65 trillion in debt through special purpose vehicles and other off-balance-sheet structures, exceeding the US$1.35 trillion they report directly, according to Nikkei.
What to Watch
AI outlook — possibilities, not facts
Regulators will increase scrutiny of AI financing structures and off-balance-sheet arrangements
Likely · Within months
Some AI companies may face financial strain if revenue growth fails to outpace financing costs
Possible · Within months
Open Questions
- What safeguards exist to prevent systemic collapse in the AI financing ecosystem?
- How will regulators respond to the growing debt and off-balance-sheet exposure of hyperscalers?
- What happens if AI revenue growth slows relative to financing costs?






