Artificial Intelligence is shaking up one of the oldest and most profitable businesses in the global financial system.
For decades, banks have quietly profited from the money sitting idle in their customers’ accounts.
You know that checking account balance you barely touch?
Well, it earns way more for the bank than it does for you.
But that model might be running out of time.
The launch of Muse, Meta’s new AI agent, set off alarm bells on Wall Street and sent shares of major financial institutions tumbling within hours.
The KBW Nasdaq Bank Index, which tracks the performance of leading American banks, dropped roughly 2.6% in a single day before recovering some of those losses in the days that followed.
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It wasn’t baseless panic.
The idea behind the scare is simple: if an AI agent can monitor your finances and automatically move your money to wherever it earns the most, bank profit margins start to seriously shrink.
And it wasn’t just banks feeling the hit. Stocks of consumer-facing companies like Charles Schwab, JPMorgan Chase, Booking Holdings, Expedia Group, and Arthur J. Gallagher also faced a fresh wave of concern over so-called AI-driven disruption.
And the market already has a concrete example of how this can play out in practice, even before AI entered the game more aggressively. 👇
The Idle Money That Keeps Banks Running
To understand the scale of the problem, it helps to step back and look at how banks actually make money from customer deposits. When you leave your money in a regular checking account, the bank takes that cash and lends it out to other individuals or businesses at much higher rates. The difference between what the bank pays you to keep your money there, which is often zero or close to it, and what it charges borrowers is called the net interest margin. This spread has been one of the main profit engines for the banking industry for centuries, and it works so well precisely because most people simply don’t pay attention to what happens with their idle cash.
In the United States, major banks accumulated trillions of dollars in deposits during the low-interest-rate era. When the Federal Reserve started raising rates, financial institutions deliberately dragged their feet on passing those gains along to account holders. While yields on U.S. government bonds climbed, checking accounts, savings accounts, and brokerage accounts kept paying next to nothing. That created an extraordinary profit window for banks, which captured billions in interest income without needing to offer anything in return to depositors. It’s a model that depends, in large part, on consumer inertia: the natural tendency people have to not switch banks, not shop around for better yields, and not move their money around frequently.
This passive consumer behavior has always been treated as a kind of invisible asset by banks. The more inert the customer, the more predictable and profitable the deposit. But the arrival of artificial intelligence agents capable of acting autonomously on behalf of users represents the exact opposite: a customer who will never be passive again, because an AI is working to make sure every penny is in the most advantageous place possible. And that’s where the equation starts to shift in a structural way.
How AI Could Change the Deposit Game
What Muse, the AI agent unveiled by Meta during its Meta Connect event, brought to the table isn’t just another cool tech feature. The app can connect a user’s financial accounts, monitor balances and investments, offer recommendations, and even execute actions on the person’s behalf. It opens up the real possibility of an automated system that continuously analyzes financial market conditions, compares yields across different institutions, identifies opportunities, and moves money without the user needing to lift a finger.
Imagine an AI connected to your accounts that, upon noticing another platform is offering a higher return on deposits, simply moves the funds over there, quietly and efficiently, at the right time and at the lowest possible cost. That level of automation transforms the financial behavior of billions of people in one fell swoop.
According to analyst Ebrahim Poonawala at Bank of America, rapid adoption of Meta’s new app opens the door to what’s known as margin compression. In a note to clients, he pointed out that the real proof that agentic AI is changing consumer behavior would come in the form of higher deposit costs for banks. In his words, until deposit costs rise faster than can be explained by rates or competition, the disruption thesis remains merely conceptual.
Financial technology had already taken some steps in this direction before AI arrived with this much force. Rate comparison platforms, high-yield accounts offered by fintechs, and personal financial management tools had been gradually chipping away at the advantage traditional banks held thanks to customer inertia. But those solutions still required action from the user: they had to research, compare, decide, and execute the transfer. With autonomous AI agents, that friction disappears completely. The system acts, and the user just sees the result. That difference might seem small, but from a behavioral and economic standpoint, it’s huge.
For banks, the scenario taking shape is one of much fiercer competition for deposits, because they’re no longer just competing against customer inertia — they’re competing against algorithms that never sleep, never forget to compare rates, and never feel too lazy to move the money. That means to retain deposits, financial institutions will need to offer far more competitive terms, which will inevitably compress the profit margins that for so long depended on exactly the opposite. 📉
What Already Happened Before AI Showed Up in Force
There’s a case that illustrates perfectly how the simple ease of moving deposits can rattle the banking market. In 2023, Charles Schwab faced intense pressure from so-called cash sorting — the movement in which customers transfer idle money from low-yield accounts into more profitable alternatives like money market funds. As interest rates climbed, account holders moved billions of dollars in search of better returns. That sudden shift forced the company to tap into more expensive short-term funding sources, which dragged down profits throughout the year.
Poonawala, at Bank of America, sums up the industry’s concern well. According to him, deposit sorting — understood as the frictionless movement of excess liquidity into higher-yielding alternatives — poses a real threat to the sector’s net interest margins. And it’s precisely that friction that artificial intelligence promises to eliminate.
That episode was an important warning. It showed that digitization had already significantly reduced the friction in moving money and that banks weren’t fully prepared to handle the speed that the digital environment demands. Now, with artificial intelligence poised to eliminate whatever friction remained, the banking sector faces a challenge on a much larger scale. It’s no longer just about how fast a customer can leave — it’s about the fact that they may not even need to consciously make the decision. The AI does it for them, continuously and optimally.
The combination of more mature financial technology, regulations that favor the portability of financial data — like Open Finance in Brazil — and increasingly capable AI agents creates an environment where the traditional model of capturing profit margins through cheap deposits becomes harder and harder to sustain. Banks that recognize this transition early and adapt, whether by offering better terms or developing their own AI-powered solutions, stand a better chance of making it through this shift without major losses. 🤖💰
What’s at Stake for the Financial Sector
The AI threat comes at a time when competition for deposits was already heating up. With the Federal Reserve raising interest rates, the pressure on banks to pay higher yields to customers has increased significantly. At the same time, institutions are hungry for more deposits as loan growth has picked up speed. To make things even trickier, the personal savings rate in the United States is near a four-year low, adding yet another constraint to the funding environment.
Bank profit margins don’t rely solely on cheap deposits, but that component is significant enough that any threat to it gets taken very seriously. A meaningful migration of deposits toward platforms offering better returns could force banks to substantially raise the rates they pay account holders just to compete, directly cutting into profitability. Add to that the fact that artificial intelligence is also being used by fintechs and investment platforms to create increasingly attractive and personalized products, and the competitive landscape gets even more complex for traditional institutions.
On the other hand, banks themselves aren’t standing still. Major institutions are already investing billions in financial technology and in their own artificial intelligence initiatives, both for operational efficiency and for improving the customer experience. The challenge is that the pace of innovation in the open AI ecosystem — with players like Meta launching powerful tools accessible to developers and consumers — tends to outpace the speed at which large corporate structures, burdened with far more layers of regulation and compliance, can adapt. That creates a window of vulnerability that could be exploited before the banks’ internal responses are ready.
What the Muse announcement did, in practical terms, was make this discussion much more concrete and urgent. Wall Street didn’t react out of fear of the distant future, but out of the realization that the future arrived faster than expected. Artificial intelligence applied to personal finance with the ability to act autonomously is no longer science fiction or an experimental prototype. It’s a reality that’s starting to take shape, and the banking sector will need to respond to it with considerable creativity and agility to protect the profit margins that for so long seemed absolutely untouchable. 🏦⚡
