Finance is YMYL, the category where a wrong answer costs real money. So Google and the AI engines weight trust, expertise, and accuracy far above keyword volume. We build the E-E-A-T signals, rank your rates and comparison pages, get them cited correctly in the AI answer, and watch what ChatGPT and Google’s AI Overview say about your regulated products.
Finance is YMYL, your money or your life, so Google and the AI engines hold these pages to a higher bar. A keyword page from an anonymous author does not rank when the topic is someone’s mortgage, their savings, or their cover. What ranks is credentialed authorship, accurate numbers, clear sourcing, and a reputation the engines already trust. That is where finance SEO lives, across lending and neobanks, payments and PSPs, wealth and robo-advisors, insurtech, BNPL, and high-scrutiny segments like crypto.
The twist in 2026: AI assistants now quote your rates, fees, and eligibility back to customers with no compliance review, functioning like a financial promotion nobody approved. Rank the trust pages and you win the click. Feed the engines accurate signals and you win the answer, and you stop the wrong number going out in your name.
Most engagements run all six together. You can scope a single track if that’s where the gap is. Each links to how we run it.
The trust layer YMYL demands, the standard Google's Search Quality Rater Guidelines spell out for money topics. We build named authors with real credentials, expert review bylines, and the transparent fee and risk disclosures Google and the AI engines reward in regulated finance.
How we run it →The pages where accounts get decided. We build and rank your /rates, /vs, and eligibility pages with accurate, sourced, current numbers, marked up with FinancialProduct schema so lenders surface correct APR and so AI engines quote your terms the way a customer would read them on Bankrate.
How we run it →Crawl, render, and Core Web Vitals, plus the layer finance programs skip: FinancialProduct and FAQ schema, llms.txt, and parser-friendly markup so engines can read your terms and trust your numbers.
How we run it →Authority in finance is borrowed from sources the engines already trust. We earn placements in review sites, editorial, and the financial publications AI assistants pull from to vet a lender or insurer.
How we run it →AI cites third parties more than your own domain. We place factual, compliant content in the comparison hubs and explainer outlets, the Bankrate and NerdWallet tier in the US and MoneySuperMarket in the UK, the engines quote when a customer asks who to bank or borrow with.
How we run it →Finance prospects vet you in r/personalfinance and niche threads, and AI engines read those threads to build trust. We earn a credible, non-salesy presence in the communities that shape your reputation.
How we run it →A generalist agency can rank your rates page and never know whether the AI answer quotes those rates correctly, or at all. We built the instrument that sees both. Software plus done-for-you execution, tuned to a regulated category, not a dashboard you operate alone or a deck with no data behind it.
Geology tracks your citation share across ChatGPT, Perplexity, Gemini, Copilot, and Google AI Overviews every week, and flags where an engine quotes your rates, fees, or eligibility incorrectly. Every page we build is briefed from what the data shows. You are never paying to rank a page while an AI assistant hands a customer the wrong number in your name.
No junior hand-off, no separate content, technical, link, and GEO vendors who never talk. One team owns the trust pages, the schema, the citations, and the measurement, and routes every regulated claim through your compliance reviewers before it ships. Final sign-off stays with you. That is how the pages stay accurate enough for the engines, and the regulators, to trust them.
We inventory every page that decides an account (rates, pricing, eligibility, security, comparisons, reviews) and the prompts your customers type into five AI engines. Then we score where you rank, where you are cited, and whether the engines quote your APR, fees, and terms accurately today, page by page, against the Bankrate and NerdWallet comparison pages that own the SERP above you.
Crawl, render, Core Web Vitals, plus FinancialProduct schema with accurate APR, rate, and fee structured data, FAQ markup, llms.txt, and parser-friendly terms. Most finance sites have strong products and a citation-unfriendly stack that hides their numbers from the engines. This layer unlocks everything built on top of it.
Your rates, comparison, eligibility, and security pages, written with credentialed authors, accurate sourced numbers, and disclosure-ready language, then routed through your compliance reviewers before they ship. In a YMYL category the Search Quality Rater Guidelines set the trust bar, so credentialed authorship and clear sourcing are not decoration, they are what ranks.
AI trusts review sites, editorial, and comparison hubs more than your own domain. We earn placements in the financial publications, aggregators like Bankrate, NerdWallet, and MoneySuperMarket, and the communities the engines already pull from to vet a lender or insurer, without sounding like a vendor in someone else's thread.
Organic applications and account opens by landing page, branded-search lift, and citation share by prompt across all five engines, with every misquoted APR, rate, or term flagged for correction. We report to the revenue line and the accuracy line, not the rankings page.
Run a Live Audit. We pull your brand against competitors on the customer prompts that matter across ChatGPT, Perplexity, Gemini, Copilot, and Google AI Overviews, flag where the engines quote your products inaccurately, and send the full report to your inbox.
