009 Agency is a fintech SEO agency built around Generative Engine Optimization: we make payment gateways, card issuers, treasury platforms and on-ramps visible, cited and chosen inside AI answers across ChatGPT, Claude, Gemini, Perplexity, Grok and DeepSeek — and we re-measure it every two weeks against a logged baseline. In fintech the question a buyer asks is rarely “who is best”. It is “is this company safe to send money to”, and the engines answer it whether you are in the room or not.
Fintech and payments is the second-deepest bench in our dataset: nine audits across payment gateways, virtual cards, stablecoin treasury, crypto off-ramping, an AI-CFO product, a tokenization platform and a personal-finance publisher, measured in the US, UK, Germany and the UAE. Eight of the nine had the same problem, and it was not visibility.
why fintech loses in AI answers specifically
The general failure pattern holds everywhere: known but not recommended. In our published dataset 93% of brands were described accurately by AI and only 4.5% were named when a buyer asked who to pick. Fintech adds a sharper version of it, because the engine is not just choosing a vendor, it is issuing a verdict about money.
the verdict problem: known, described accurately, then flagged
A virtual-card issuer we audited was described in depth by both ChatGPT and Perplexity — product, limits, use cases — and both answers ended with “not independently verified” and a due-diligence checklist for the buyer. Unprompted, both engines flagged that the terms said one jurisdiction and the company profiles said another. A crypto card with brand recall on all four engines, rare for a seven-month-old domain, received a negative trust verdict on all four: “start with $10–25”. This is a different failure from being unknown. The engine has read everything about you and decided to warn the customer.
cited as the source, recommended as nobody
A tokenization platform we audited is already a source domain in the engines’ citation graph — Perplexity cited its jurisdiction guide as the reference on a real-estate tokenization question — and then named six vendors, one of them a competitor the platform has its own comparison page about. ChatGPT’s own search log showed it querying six competitors’ sites by name and never the platform’s. Not rejected: never considered. The company was doing the category’s homework and the competitors were collecting the leads.
app-like frontends split the engines against you
A stablecoin business-account product gave us the cleanest measurement in the set. One prompt, its own feature list verbatim, run on three engines: Gemini named it first, “the most direct match”, with twelve citations of its site. ChatGPT and Perplexity did not name it at all and suggested that no such product might exist. The only variable was that Gemini grounds on Google’s index, which executes JavaScript, and the other two fetch the page live and do not. The product was there; two of three engines received an empty shell.
where we work inside fintech
| segment | what the audits keep showing |
|---|---|
| payment gateways | A rebrand without a migration leaves the citations, the trust and the AI answers with the old brand. One gateway is out-ranked two to three times on every market by the company it split from; the engines still name the parent first. |
| cards and issuing | Trust verdicts decide the answer. Jurisdiction conflicts between terms, profiles and directories are found by the engines on their own and read out to the buyer. |
| stablecoin treasury and payroll | Client-side rendering removes the product from two of three engines. Gemini sees it; ChatGPT and Perplexity see a container. |
| on- and off-ramps, private banking | Demand lives in a different language than the site. One Swiss intermediary had 22 monthly visits in English and zero in German, where the category is ten times larger and every competitor is present. |
| tokenization and RWA | Cited as a reference, absent from the shortlist. The company’s guides are the engines’ source; the recommendation goes to whoever is on the lists. |
| early-stage products and finance media | Three different descriptions of the company across the site, the funding database and the profiles — and the engines blend them into a fourth. For publishers, a near-identical domain absorbs the brand answer. |
what the first 90 days look like
The order is the same as everywhere, because it has to be: readable, then verifiable, then quotable.
- Audit. The trust prompts and category prompts your buyers actually ask, run live through the engines and logged verbatim, plus crawler checks with real AI user-agents and a rendering test per engine. You get a health score, the verdicts engines currently give about your company, and the three most expensive gaps. Complimentary. what is inside →
- Make the trust layer machine-readable. One entity, one jurisdiction, one set of fees, licences a crawler can fetch, the founders’ records resolving to live pages, and the frontend rendered for engines that do not run JavaScript. Shipped as files your developer applies. technical GEO →
- Publish what gets quoted. Fee and limit pages, jurisdiction and legality pages, and the comparisons buyers ask for — written to be liftable in one paragraph, with the stablecoin and use-case pages the category is missing.
- Get onto the lists. The roundups, directories and communities the engines actually cite in your category and language — identified from your own panel, not from a generic outreach list.
- Re-measure. Same panel, every review, reported as a delta. Series, not screenshots.
proof, and its limits
The fintech bench is nine audits and no client on retainer yet, so every number on this page is an audit measurement, not a program result. The measured result we can point to comes from the neighbouring vertical: a crypto-law client went from 0/5 to 4/5 engines naming it on its category prompt by day 17 (July 2026), with the log published. Fintech trust verdicts move by the same mechanics — readable licences, one entity, named humans — and we will show you the audit answers, including the warnings, before you decide anything.
one thing we will not do
We will not publish a fee, a licence or a jurisdiction we cannot verify. In one audit the site said 1% on the about page and under 1.5% on the product pages, and the engines quoted both. In another, a regulatory suspension claim from a third-party forum was circulating in brand answers; we did not repeat it to the client as fact and we would not put a rebuttal on the site that the record could not back. In fintech, one inconsistency is enough for the engine to switch from recommending to warning.