AI assistants helping people maximize their cash could trigger a bank run, Apollo's chief economist warns

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Published: 2026-09-28T14:56:12.036Z • Permanent link

Apollo Global Management's chief economist, Torstein Slok, has warned that the increasing use of AI assistants to help people manage their finances could trigger a bank run. Slok's theory is based on the idea that these AI agents are shifting large amounts of money around, creating a ripple effect that could lead to a massive exodus from traditional banking institutions. This warning comes at a time when the use of AI-powered financial tools is becoming increasingly widespread, with many consumers using apps and online platforms to manage their finances.

Slok's theory is rooted in the concept of "behavioral finance," which suggests that people's financial decisions are influenced by their emotions and psychological biases. In this context, the use of AI assistants could be seen as a way to automate financial decisions, reducing the role of emotions and biases in the decision-making process. However, Slok argues that this could have unintended consequences, such as creating a self-reinforcing cycle of behavior that ultimately leads to a bank run. For example, if people become too reliant on AI-powered financial tools, they may become complacent and less likely to seek advice from financial experts, leading to a loss of financial literacy and a greater risk of financial instability.

The potential impact of Slok's theory is significant, with major banks and financial institutions already investing heavily in AI-powered financial tools. For instance, Goldman Sachs has launched a range of AI-powered financial products, including a robo-advisor that uses machine learning algorithms to manage investment portfolios. Similarly, JPMorgan Chase has developed an AI-powered platform that uses natural language processing to help customers manage their finances. While these developments may seem exciting, Slok's warning suggests that they could ultimately contribute to a more unstable financial system.

Slok's warning has significant implications for the data sources that underpin our understanding of the financial markets. One of the key data sources that will be affected is the Federal Reserve's Financial Stability Report, which provides a comprehensive overview of the US financial system. The report is based on a range of data sources, including banks' balance sheets, credit defaults, and other financial metrics. However, if Slok's theory is correct, the use of AI-powered financial tools could create a new type of risk that is not currently captured by these data sources. For example, if people become too reliant on AI-powered financial tools, they may be less likely to seek advice from financial experts, leading to a loss of financial literacy and a greater risk of financial instability.

Another key data source that will be affected is the research community, which has been studying the impact of AI-powered financial tools on financial markets. Researchers at institutions such as the University of Chicago and the Massachusetts Institute of Technology have been exploring the potential benefits and risks of AI-powered financial tools, including their impact on financial stability. However, if Slok's theory is correct, these researchers may need to revisit their assumptions and develop new models to capture the potential risks associated with AI-powered financial tools.

The idea that AI-powered financial tools could trigger a bank run is not new, and has been explored by researchers and policymakers in the past. For example, in 2018, the Bank of England published a report that warned about the potential risks of AI-powered financial tools, including their impact on financial stability. However, the report also acknowledged that the benefits of these tools, such as improved financial literacy and reduced costs, could outweigh the risks. Similarly, in 2020, the European Central Bank published a report that explored the potential benefits and risks of AI-powered financial tools, including their impact on financial stability.