• AI visibility

Guide · AI search

Are AI assistants changing how banks and finance teams choose fintech software?

Yes: business buyers, including finance teams and bank staff, now use AI assistants to research vendors, often inside private tools their employer provides. In finance, those assistants lean heavily on sources that already rank and on trusted third parties, and every shortlisted vendor still faces regulated due diligence. For a fintech company, AI visibility is won with verifiable proof of compliance, security and results, not with louder claims.

By Underneath Team Guide Updated

The short version

  1. Google shows AI answers on most finance searches: in our study of 800 US keywords, financial services and insurance searches triggered an AI Overview 88.0% of the time, among the highest of eight industries.
  2. Finance answers lean on established sources: in our AI Overview citation study, 34.8% of finance and insurance citations were page-one Google results, against 23.9% for B2B software, and nerdwallet.com was cited in 10.0% of all AI Overviews in the sample.
  3. Bank buyers must document every vendor choice: US banking regulators’ interagency guidance (opens in a new tab) covers “due diligence and third-party selection,” including relationships with fintech companies, and the EU’s DORA (opens in a new tab) has applied since 17 Jan 2025.
  4. A fintech customer can be worth years of recurring and transaction revenue: Q2 (opens in a new tab), which sells digital banking software to banks and credit unions, reported subscription annualized recurring revenue of $825.5 million, and BILL (opens in a new tab) served 479,300 businesses.
  5. Fintech is moving inside the assistants: Intuit signed a deal worth more than $100 million (opens in a new tab) with OpenAI to bring TurboTax, Credit Karma and QuickBooks into ChatGPT.

Which institutions and teams buy fintech software, and what is each worth?

Three kinds of buyer: financial institutions, business finance teams and consumers, each with different economics.

Financial institutions. Banks and credit unions buy digital banking, lending, payments, fraud and compliance software through formal evaluations. Q2’s second-quarter 2026 results show the stakes: subscription annualized recurring revenue of $825.5 million, up 15%, and eight Enterprise and Tier 1 contracts signed in the quarter. One of those came after a large bank acquired an existing Q2 customer. Contracts like these run for years. Our guide on getting onto a bank’s vendor shortlist looks at core, payments and fraud deals in more detail.

Business finance teams. CFOs, controllers and accounts payable teams buy spend management, payables, receivables and treasury tools, often faster and with less ceremony. BILL, which sells this kind of software, reported fiscal 2026 core revenue of $1,504.7 million across 479,300 businesses. Most of it, $1,211.2 million, came from transaction fees, so a customer’s value grows with every payment it makes through the platform. Processors that sell to merchants follow a related path, set out in how payment processors reach merchant shortlists.

Consumers. Neobanks, lenders, “buy now, pay later” providers and investing apps sell directly to people. The Federal Reserve’s 2024 household survey found use of buy now, pay later edged up to 15 percent of adults. Sensor Tower (opens in a new tab) reports credit and lending app downloads rose 18% in 2025.

This article focuses on the first two, where deals are larger and buying is more deliberate. Subscription economics outside finance are covered in how B2B SaaS companies generate revenue from AI search.

When do bank and finance-team buyers consult AI?

At the research stage, inside work tools, and increasingly inside the assistants themselves.

No public survey isolates fintech buyers, so the evidence comes from wider business buying:

Banks themselves are heavy AI adopters. The Evident AI Index (opens in a new tab), which tracks 50 of the world’s largest banks, reports that AI deployment across the sector moved nearly three times faster this year than in previous years. Teams that use AI daily in their own operations are, we infer, likely to use it when researching suppliers too.

On the consumer side, fintech now operates inside the assistant. OpenAI launched Instant Checkout (opens in a new tab) in ChatGPT, built with Stripe on an open Agentic Commerce Protocol, and says more than 700 million people use ChatGPT each week. Intuit’s apps, including Credit Karma, are coming to ChatGPT under its OpenAI deal, so users can review credit options without leaving the chat. And in Menlo Ventures’ 2026 consumer survey, 23% of Americans who pay bills already use AI to help.

Which questions do fintech buyers ask AI assistants?

Questions about fit, integrations, compliance, fees, alternatives and whether a provider can be trusted. We wrote the examples below to illustrate bank, CFO and consumer questions.

BuyerIllustrative prompt
Community bank“Which digital banking platforms do credit unions under $2 billion in assets use, and how long does conversion take?”
Bank risk team“Which fraud detection vendors for real-time payments have bank customers in the US, and what do their SOC 2 reports cover?”
Mid-market CFO“Best accounts payable automation for a 300-person company on NetSuite”
Startup finance lead“Ramp vs Brex for a Series A company with international contractors”
Controller“Alternatives to BILL for a company that pays many overseas suppliers”
Payments team“Which payment processors support the Agentic Commerce Protocol?”
Consumer“Is this savings app FDIC-insured, and what do customers say about it?”

Many of these questions reach Google first, where AI answers are now the norm. In our frequency study, financial services stayed among the two highest industries even after adjusting for the mix of searches. Google documents that its AI features may use “query fan-out” (opens in a new tab), running several related searches across subtopics before answering.

How does an AI answer lead to a bank contract or a finance-team trial?

By putting you on the first list for an evaluation, or in the answer that leads to a trial.

The bank path. A team member asks an assistant to map vendors, a shortlist forms, a request for proposal goes out, and the vendor then passes due diligence, contract negotiation and implementation. The interagency guidance describes this life cycle as “planning, due diligence and third-party selection, contract negotiation, ongoing monitoring, and termination.” The revenue is a multi-year subscription that, at Q2, also expands when existing customers add products.

The finance-team path. A controller asks for options, compares two or three tools, and starts a trial or demo. Forrester found more than 60% of business buyers use some form of trial. At a company like BILL, revenue then follows the customer’s payment volume.

The consumer path. A person asks whether an app is right and safe, checks reviews, and signs up. Here, the assistant’s summary of reputation can decide the outcome.

In all three, the AI answer comes first and the money comes much later. We suggest measuring AI visibility against the pipeline it feeds: request-for-proposal invitations, demo requests and sign-ups that name an AI assistant as a source.

What makes an assistant trust a fintech vendor enough to name it?

Mostly trusted third-party evidence; in finance, assistants and Google’s AI lean on established, well-ranked sources.

Documented by platforms: Google says its AI features can run several related searches. OpenAI says ChatGPT’s shopping results are “organic and unsponsored, ranked purely on relevance to the user,” and that Instant Checkout items “are not preferred in product results.” Neither publishes how it chooses financial software vendors.

Observed in our studies:

  • Ranking still matters more in finance. In our citation study, 34.8% of finance and insurance AI Overview citations were page-one results, against 23.9% for B2B software. Finance searches lean more on pages that already rank.
  • Named authorities get cited. In our hidden-searches study, when ChatGPT’s search named a source such as NerdWallet, the answer cited that source 44.0% of the time, against 8.1% when it did not.
  • Reputation answers come from review platforms. In our reputation study, 88.0% of answers to “Is this brand legit?” cited a review or complaint platform, and Trustpilot and the BBB accounted for 61.7% of review-platform citations.
  • Country changes the answer. In our country study, ChatGPT put QuickBooks first for small business accounting software in every US and Canadian run and Xero first in every UK and Australian run. The country mattered most for financial services and insurance.
  • Communities matter less than in software. In our Reddit study, 5.7% of Google’s AI Overviews for financial services searches cited Reddit, against 35.4% for B2B software. In our YouTube study, they cited a video on 49.0% of financial services searches, against 91.0% for B2B software.

Our inference for fintech: the trust factors are regulatory status (bank charter or partner bank, licenses, FDIC or similar protections stated accurately), security attestations such as SOC 2 and PCI DSS, named financial institution customers, coverage in finance publications and comparison sites, and clean review profiles. An assistant that cannot verify these is more likely to name a better-documented rival, we infer.

What does GEO look like when your buyers are banks and CFOs?

Generative engine optimization (GEO) makes your regulatory status, security and results easy for assistants to find, verify and repeat.

In practice, for a vendor selling to banks and finance teams, the work usually covers:

  1. Accurate regulatory facts. State on public pages exactly what you are and are not: licenses, partner banks, deposit insurance, data handling, and the markets you serve. Assistants repeat what they find, and errors here are costly. When an assistant misstates your charter or partner bank, follow how to fix wrong information about your brand in AI answers.
  2. Public due diligence material. A trust page with security attestations, uptime, incident history and policies, readable without a login, so a bank’s research and its assistant find the same proof.
  3. Search foundations. Because finance answers lean on page-one results, keep the pages that answer buyers’ questions ranking well in Google and Bing.
  4. Trusted third parties. Coverage in finance and banking publications, placement on comparison sites buyers name, analyst and peer-review profiles, and named customer stories with financial institutions.
  5. Reputation hygiene. Monitor Trustpilot, the BBB and app store reviews, respond to complaints, and fix the issues behind them; assistants summarize what those platforms say.
  6. Market-by-market checks. Test answers in each country you sell in, since assistants change their picks by market. See whether an English-only AI visibility check is enough.

No one can guarantee an assistant will recommend a fintech vendor. GEO makes it more likely that the evidence it finds is accurate, verifiable and in your favor.

What can’t the evidence tell fintech vendors yet?

It shows finance searches are full of AI answers; it does not show how banks’ private assistants pick vendors.

  • No fintech-specific buyer survey. We found no public, independent survey of how bank or CFO buyers use AI assistants to choose fintech vendors. The buyer figures above cover business buying in general.
  • Private tools are invisible. What a bank’s internal assistant answers, and which sources it may use, cannot be observed from outside.
  • Our studies are snapshots. Our citation and frequency findings come from US searches in September 2026; answers change over time and between assistants.
  • No link to revenue yet. No public study connects AI visibility to fintech contracts or transaction volume. What is known outside finance is summarized in does AI visibility drive business results.

What should a fintech vendor test before the next bank RFP?

Ask the questions your bank and finance-team buyers ask, in the assistants they use, in each market.

That first check shows whether you are named for your core use cases, which rivals and sources appear instead, and whether your regulatory, security and pricing facts are described correctly. In fintech, a wrong fact can cost a deal before a seller ever hears about it.

If your growth depends on request-for-proposal invitations from financial institutions or demos with finance teams, ask us for a due-diligence-style visibility review. We will compare how assistants describe you and your competitors, list the evidence gaps a bank’s own due diligence would surface, and propose how to close them before the next evaluation. Our generative engine optimization service page explains how that work is run for vendors selling to banks and CFOs, including public due-diligence pages, accurate regulatory facts and checks in each market.

Frequently asked questions

Are bank staff using ChatGPT to research fintech suppliers?

Many business buyers do, often through private AI tools at work. Forrester found 61% of business buyers use AI tools provided by their organization, though no public survey isolates bank buyers.

Why do AI answers about finance favor sites like NerdWallet?

Finance answers lean on established, well-ranked sources. NerdWallet was cited in 10.0% of the AI Overviews in our sample, and ChatGPT cited named sources such as NerdWallet far more often when its own search mentioned them.

Does SEO still matter for fintech AI visibility?

Yes, more than in many industries. In our study, 34.8% of finance and insurance AI Overview citations were page-one Google results, against 23.9% for B2B software.

Can a fintech company pay to appear in ChatGPT’s recommendations?

Not according to OpenAI’s documentation, which says shopping results are “organic and unsponsored” and that Instant Checkout items are not preferred in results. Visibility has to be earned through evidence.

Sources

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