FinTechs Lag Credit Unions on the Next AI Banking Test

New data from PYMNTS Intelligence found that only 1 in 3 FinTech executives say they currently offer AI-led chat support for customers of the firms they work with, in any industry.

In an era where DeepMind’s AlphaFold can map the structure of essentially every known protein and Anthropic’s Claude Code can generate what a non-computer programmer “vibe codes” in ordinary language, chat support for a bank customer or credit union member wanting to see if they qualify for a personal loan wouldn’t seem like rocket science.

After all, other industries have gone all-in. Amazon rolled out its generative-AI conversational shopping assistant, Rufus, in 2024, to help people track packages, after using earlier iterations of chat support for years. Since the COVID-19 pandemic emerged in 2020, airlines have routinely use AI-driven chatbots to help customers book flights and locate lost luggage. Ditto insurers, for quotes and policy information, claims status and customer-service requests.

But those companies and industries have the dollars to build things internally, spend big on third-party solutions or acquire startups that specialize in AI. By contrast, unless it’s a multi-billion dollar institution like Boeing Employees Credit Union ($29 billion), most credit unions don’t have the assets or expertise to build the customer-facing AI solutions that traditional banks have embraced.

In financial services, FinTechs are synonymous with companies like Plaid, whose technology allows customers of 10,000 banks and credit unions across the United States and Canada, including Chase and Bank of America, to transfer money, pay bills and link their accounts to a Venmo or Robinhood to fund payments and brokerage accounts.

But even as credit unions increasingly partner with FinTechs — a trend detailed in another recent PYMNTS Intelligence report — AI-supported chat, one of the most basic consumer-facing tools in modern financial services, is lagging.

Credit unions have been slower to adopt AI chat assistants “largely because they’re dealing with older systems, tighter budgets and more conservative implementation strategies,” said Ivan Patriki, chief marketing officer and co-founder of QuantMap. At the same time, he added, “most FinTechs still use AI at the surface level. They can answer questions, but they can’t yet make payments smarter or provide truly personalized financial guidance at scale.”

Only 1 in 4 credit unions currently offer AI-fueled support for their members. What’s striking is that FinTechs aren’t much further ahead: Just 32% offer tools with AI-driven support for customers of the companies they work with.

It looks even stranger when you consider the other artificial intelligence support services FinTechs are currently able to offer. Only 16% of FinTechs offers products with AI financial advice, roughly on par with credit unions, at 17%. For AI payments, FinTechs are behind the curve: Just 12% offer that capability versus 16% of credit unions, at 16%.

True, going from a chat assistant that shows your account balance to one that offers financial advice is a heavy lift. “AI financial advice will move slower because the regulatory risk is much higher,” said Andrey Lebedev, founder of Swipelux, a payment infrastructure company.

Still, the FinTech numbers invite an obvious question: Why? These aren’t companies constrained by legacy mainframes or a reluctance to upset branch managers. They were built from scratch by engineers whose explicit mandate was to do things banks couldn’t or wouldn’t do. The technical challenge of an AI chat interface is, by their standards, not especially steep. Many of them have already built more complex systems — real-time fraud detection, algorithmic underwriting, payment rails processing millions of transactions daily.

When it comes to AI chat support, there’s an odd disconnect between the technologically forward status of FinTechs and the old-school infrastructure legacy of most credit unions. As Anoop Gala, senior vice president at Infinite Computer Solutions, and head of its banking and financial unit, told PYMNTS, “Many credit unions are still working through challenges related to implementation, integration with legacy systems, limited technology budgets and ensuring that AI-driven interactions align with the high-touch, relationship-focused service model that members expect.”

The PYMNTS Intelligence data offers a partial answer to the “why” question. When FinTechs rank their innovation priorities, AI automation comes in fifth. Data security ranks first, at 70% of respondents. Analytics ranks second, at 61%. Compliance is third, at 60%. New payment tools comes in fourth, at 53%. AI sits behind all of them.

Half of FinTechs say AI automation is a priority — they project reaching 72% on AI chat by 2032, equal to 40 percentage points of growth over six years, or roughly the next two product cycles.

Credit unions show the same pattern, perhaps more starkly: Half name AI conversational tools as a member acquisition strategy, then rank AI agents ninth in their actual budgets.

If FinTechs are only marginally ahead on the most basic capability and behind on the rest, the partnership model’s ability to close the demand gap is more limited than the credit union industry’s investment thesis may assume.