AI tops the risks to US financial stability in Federal Reserve survey of market contacts
AI was the most frequently cited risk to US financial stability in a survey of market contacts published in the Federal Reserve's November Financial Stability Report on November 13. Staff at the Federal Reserve Bank of New York collected the views of 23 contacts at broker-dealers, banks, investment funds and advisory firms in September and October. Mentions of AI, higher long-term interest rates and cyberattacks rose the most compared with the spring survey.
Respondents named three areas of concern. The first is a sharp correction in AI-related stocks, driven by uncertain returns on large capital spending; many said stretched valuations, circular financing arrangements and heavy reliance on debt to fund the AI buildout could amplify losses and spill over into business investment and household consumption. The second is cybersecurity, from attacks by sophisticated state actors or damage caused by frontier AI models themselves, as advances in AI lower the barrier to sophisticated attacks. The third is complex forms of AI-related financing.
Cyberattacks and fiscal debt sustainability were seen as the risks with the most severe potential consequences. The report says the survey summarises respondents' views and does not represent the views of the Federal Reserve Board or the New York Fed.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Finance AI Weekly, Cybersecurity AI Weekly or Daily AI Brief.
Also, consider following us on social media:
More from Finance
Nov 15 California insurance regulator starts work on AI consumer safeguards with insurer survey and public workshop Nov 13 DNB moves customer service to Genesys AI, with 80% of AI summaries accepted unedited Nov 13 Osaic to pilot Anthropic's Claude for Financial Advisors Nov 13 OpenAI launches ChatGPT Wallet so AI agents can pay without seeing your card Nov 13 Free chatbots miss key points in financial advice for low-income families, benchmark findsMore from Cybersecurity
Nov 15 Cohere completes AISLE acquisition and buys AI code review startup cubic Nov 15 Anthropic hired 33 counterintelligence staff this year as AI labs court former spies Nov 14 White House AI task force urges 12 months of liability relief for companies that report cyber incidents Nov 14 FBI warns ARTEX lets attackers automate intrusions at machine speed Nov 14 Protegrity releases open-weights model for finding personal data in AI workflowsFinance AI Weekly
Weekly newsletter about AI in finance. Covers AI-driven trading, fintech innovations, and data analytics transforming markets
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
Australia's bank regulator will stress-test the financial system for AI risks next year
Fed Governor Barr warns AI could concentrate gains among a few firms and widen inequality
MIT study finds many large companies do not disclose AI risks
S&P Global Warns of Hidden AI Debt at Major Tech Companies
Fed economists find AI boosts data center investment but has little effect on jobs and productivity so far
Daily AI Brief: the AI news that matters, in your inbox.