AI agents may cause banks to run out of money: Wall Street warns of low cost deposit crisis

According to Woofun AI, Apollo Group's chief economist Thorsten Slocke issued a severe warning that Muse, an AI agent launched by Meta (META.US), may trigger a new type of crowding crisis targeting the traditional banking industry through automated fund allocation. Slock pointed out that this type of intelligence has gone beyond the scope of a simple information question-and-answer tool and evolved into an assistant capable of performing complex financial operations on behalf of users. Once this technology is popularized on a large scale, the low-cost deposit base on which banks depend will completely collapse, thus posing a serious challenge to the stability of the entire financial system.

The underlying reason lies in the combination of the lure of huge spreads and automated execution capabilities. Currently, the US Federal Deposit Insurance Corporation (FDIC) data shows that the national average interest rate for checking accounts is only 0.1%, while the average interest rate for savings accounts is as low as 0.4%. In contrast, there are plenty of high-yield alternatives on the market. Slock listed 11 types of fintech products and online bank accounts with returns between 3.3% and 5%. Among them, Adelfi offers a yield of up to 5%, followed by SoFi (SOFI.US), with a yield of 4.5%.

According to data compiled by Woofun AI, this spread is extremely attractive to ordinary savers: in the case of a $10,000 deposit, held in a checking account with a 0.1% interest rate, the annual income is only about $10; if transferred to an account with a 5% interest rate, the annual income jumps to about $500. The core logic of bank profits is interest spreads formed by using low interest rates to absorb deposits and issue loans at high interest rates.

However, if every household uses AI intelligence to optimize returns on cash assets, banks will lose low-cost funding sources for lending, and this structural imbalance will undoubtedly cause serious problems for the financial system.

It is worth noting that market reaction and technology implementation are accelerating this process. Meta (META.US) officially launched Muse on September 8, and data service company Plaid is responsible for connecting it to more than 12,000 US financial institutions and applications. Plaid said that users can check account balances, transaction records, investment status, and mortgage details through the smart device. Although it is not clear whether it has a cross-account transfer function, Slock is convinced that this kind of fund transfer “will happen soon.” JPMorgan Chase (JPM.US) raised Meta (META.US)'s target share price on Thursday, believing that Muse is expected to become the most popular consumer-grade AI application after ChatGPT.

Industry opinions also confirm this trend. Chartered financial analyst Mike Zaccardi has deposited cash into a BOXX ETF fund designed to track short-term US Treasury bond returns, and warned that if everyone starts using such AI assistants to automatically transfer funds from 0.1% checking accounts to 5% high-yield accounts, banks will lose their low-cost deposit base, which in turn will cause a crisis in the financial system. Nate Gerage, co-founder of the ETF Research Institute, further pointed out that artificial intelligence and cryptocurrencies together pose a threat to traditional banking models, and that politicians should actively accept, rather than resist, this irreversible technological change.

Uncertainty at the policy level has heightened market anxiety. There is a heated debate in Washington over who has the power to decide interest rates on depositor deposits, focusing on the “Clarity Act,” which is trying to be restarted. The bill failed in a Senate procedural vote on September 15, with the stablecoin yield issue at the core of the controversy.

Although Slock's report did not give a specific estimate of the size or speed of money transfers, the logical chain it revealed clearly shows that technology-driven money optimization is reshaping the underlying logic of the banking industry. Following the impact of cryptocurrencies on traditional payment systems, this is yet another structural challenge posed by artificial intelligence on the bank's debt side. Its ultimate impact depends on a game between regulatory response speed and technology penetration rate.