BankThink

The AI prompt that could wipe out banks' net interest income

BankThink on financial revolution
It won't be long before bank customers can ask an AI agent to optimize their returns on idle cash. When it happens, banks' net interest income is going to come under direct threat, warns Michael Abbott, of Accenture.
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When JPMorganChase CEO Jamie Dimon speaks, the industry listens. His comments on competition at this year's World Economic Forum were telling.

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Fintechs aren't letting up: "They're coming at you, some to pick a sliver of the business, some to take your whole business."

AI could restructure customer access and product delivery. "Agents … may lead to us winning and losing big areas."

Banks could face significant losses if they fail to adapt. "If you put your head in the sand, you will lose."

The future of competition for banks will be fierce in 2026. However, I believe a new class of competitors will emerge that attack banking from the outside-in and target the balance sheet.

The last 25 years of fintech disruption have seen fintechs attempt to mimic banks and compete for the same services. They've seen limited gains: After 25 years of digital not a single neobank has cracked the global top 200 banks by assets.

With the emergence of AI engines, we see a very different competitive landscape emerging, with tech companies that attack both sides of the balance sheet but never touch banking itself. They will be infinitely more disruptive than fintechs already operating within the system.

It won't be long before customers can ask their favorite GPT engine this simple question: "Help me optimize the return for my idle cash." That one prompt takes direct aim at deposit beta in the U.S banking system.

Many customers in the U.S. are ready for it: Seventy-one percent say they would use an "everywhere" AI financial assistant that helps manage all their banking relationships, and 55% would trust a generative AI platform to own that experience, according to Accenture's recent Future of Banking Experience survey.

Even a relatively small shift in pricing could lead to a 5% drop in lending margin and 15% drop in deposit margin, putting around 22% of U.S. banking pretax income at risk, according to Accenture Research.

What's changed? In the search engine model, when a customer needed to apply for a mortgage, the search engine would share links to mortgage providers. The quid pro quo was that banks published their websites, let the search players take the data and then presented the banks' websites to customers.

Eightfold AI, which many companies use as they screen job candidates, is being accused of gathering information about applicants without their consent. The lawsuit also alleges that the company uses an algorithm to judge candidates without explaining how it works.

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Job candidate being interviewed by a robot

In the GPT world, the GPT does all that work behind the scenes, figures it out for the customer and presents the offers. This simple but important shift in the way consumers interact online from search to prompt will force banks to ask some interesting questions.

First, what products, services and experiences do they want to own and never expose to prompt engines to protect their brand?

For the products that banks want to expose, how can they redesign their interfaces to interact directly and efficiently with GPT engines to assure top-of-prompt positioning, a term that most banks aren't even thinking about today.

No one knows for sure how this will play out, but banks should consider offensive and defensive moves to make in this competitive landscape.

If they want to play offense, they could strike first by creating their own rate-optimization engines within their mobile banking apps. This could extend to the wealth side as well, with an AI engine that shows customers how to achieve the same returns with lower funds. This helps to build a stronger, more trusted relationship with customers and could limit the financial hit in the long term from GPT engines.

Banks could also partner directly with these GPT engines. For example, PayPal is partnering with OpenAI to support payments processing, enabling ChatGPT users to use a PayPal checkout button to pay for their purchase online without leaving the conversation with the AI bot. Similarly, in Germany and Italy, BBVA has created an app within ChatGPT that allows customers to explore its banking products.

If they want to play defense, banks can design more customer-centric products. By eliminating existing product silos — with separate deposit and lending solutions — banks can focus on the customer's full relationship. They can create offerings that reward customers for the totality of their relationship, combining products into integrated offerings that AI agents can't as easily disintermediate.

The other thing that can't be underestimated in the age of large language models is having a physical presence. Data consistently shows that consumers of all age groups like having a branch near them and use them to solve more complicated problems. Banks should continue investing in these locations — transforming them more into advice hubs or embracing micro-booth formats — while keeping day‑to‑day customer journeys fully digital.

We think 2026 will be a pivot point where the competition of old is not going to be the competition of the future. Banks have already ceded the payment experience to digital wallets, who are an API away from collapsing mobile app traffic if they surface account balances and financing offers inside the wallet — with agents likely to intensify that shift by presenting embedded financing at the point of intent.

They can't afford to lose the banking experience to a new set of tech players.

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Artificial intelligence Bank technology Fintech
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