Apollo Economist Warns of AI-Driven Bank Run Risk

The potential for an 'agentic bank run' could disrupt traditional banking systems and impact credit availability.

• On September 27, 2026, Torsten Sløk, Chief Economist at Apollo Global Management, warned about a possible 'agentic bank run' driven by AI.
• AI tools like Meta's Muse could automate the migration of deposits from low-yield bank accounts to higher-yield fintech platforms.
• The current interest rate gap—0.1% for traditional accounts versus up to 5.0% at fintechs—could lead to a systemic shift in deposit behavior.

• Traditional banks have relied on low-cost deposits to fund loans, with an average interest rate of just 0.1% on checking accounts.
• Fintech platforms have been attracting consumers with significantly higher interest rates, ranging from 3.3% to 5.0%, leading to gradual shifts in consumer behavior.
• Advancements in AI allow for real-time monitoring and automated transfers, making it easier for consumers to optimize their deposits without manual intervention.

Torsten Sløk's analysis highlights a critical shift in the banking landscape, driven by the rise of agentic AI. Unlike traditional bank runs, which are often fueled by panic, this potential 'agentic bank run' would stem from efficiency-driven automation. With AI tools capable of monitoring interest rates and account balances in real-time, consumers could see their deposits migrate almost instantaneously to higher-yield options without any active decision-making on their part.

The existing interest rate disparity is already prompting a gradual migration of funds from traditional banks to fintech platforms. For instance, a $10,000 balance in a traditional checking account earning 0.1% would yield just $10 annually, while the same amount in a fintech account earning 5.0% would generate $500. This stark difference in potential earnings is a significant incentive for consumers to shift their deposits.

As AI becomes more integrated into financial decision-making, the risk of systemic shifts increases. Sløk's note suggests that if a large number of consumers begin using AI agents to optimize their deposits, banks could face a rapid depletion of their low-cost deposit base. This could force banks to raise interest rates to retain customers or seek more expensive funding sources, ultimately impacting credit availability for consumers and businesses alike.

The implications of this shift are profound. If banks lose their low-cost deposits, they may struggle to maintain their lending practices, leading to tighter credit conditions. This could affect everything from personal loans to mortgages, making it more difficult for consumers to access financing. Furthermore, the Bank of England has previously warned about the risks of AI-induced herding in markets, indicating that this is not just a localized issue but a potential global concern.

• Consumers with savings: Those with significant deposits in traditional banks may see their interest earnings diminish as banks react to deposit outflows.
• Traditional banks: Banks that rely heavily on low-cost deposits for lending could face financial strain and increased operational costs.
• Fintech platforms: These companies may experience a surge in deposits, leading to increased competition in the financial services market.

• Regulatory responses: Keep an eye on how financial regulators respond to the potential risks posed by AI in banking.
• Interest rate adjustments: Monitor changes in interest rates offered by traditional banks as they react to deposit migrations.
• Consumer behavior trends: Watch for shifts in consumer behavior regarding banking choices, particularly as AI tools become more prevalent.