Neobanks, fintech apps, lending, and payments compete in the second-strictest YMYL category — financial. We engineer the trust, schema, and citation surfaces that win both Google's E-E-A-T bar and AI Mode eligibility.
Financial buyers ask AI before they ever apply. Google holds fintech to a strict YMYL bar — and AI Overviews are even more conservative about which financial brands they cite. The fintechs winning have engineered every product page, every author, and every comparison surface to clear both bars.
Every comparison and product page gets a verifiable financial writer + reviewer entity — credentials, sameAs links, and matching schema. AI refuses to cite unsigned financial content; we fix that at the source.
Layered FinancialProduct, Offer, FeeSpecification, AggregateRating, and Review schema — engineered for rich results and AI Overview citation on rate, fee, and feature queries.
Fintech buyers compare obsessively. We engineer comparison pages (vs competitor, vs alternative, vs traditional bank) with citation-dense answer blocks that AI extracts verbatim.
AI Overviews answer "best high-yield savings," "top business checking," and "cheapest stock broker" with named brands. We engineer the entity, citations, and answer blocks that get yours named.
We can promise this because our methodology already works. Hundreds of pages now sit in position #1 across our clients' catalogs. The risk shouldn't be on you — it's on us.
Neobanks, lending, payments, investing, crypto-adjacent, BNPL, and B2B fintech all fit the framework. The schema and entity work differ slightly by sub-vertical.
Our audit identifies every product and comparison page that lacks the E-E-A-T scaffolding (author entity, reviewer entity, citations, disclosure). We prescribe the smallest set of fixes to restore citation eligibility.
Yes — for specific product categories (high-yield savings, business banking, brokers), AI Mode increasingly returns named brands with rate + fee detail. Brands without entity + schema work get skipped.
Three layers, in order. First, entity clarity: one canonical Organization with @id anchors, sameAs links to authoritative databases, and knowsAbout coverage of your real expertise. Second, extractable content: atomic answer blocks, comparison tables, transparent pricing and specs, and FAQ blocks on every commercial page. Third, corroboration: mentions in the roundups, directories, review platforms, and trade publications those engines retrieve. Measure it by probing a fixed set of buying questions monthly and tracking citation frequency per engine.
Citability. AI engines lift passages that answer one question completely in 40–80 words, in plain language, with a concrete number, definition, or list. Pages that bury the answer under narrative rarely get quoted. We rewrite key pages so every important question has a self-contained answer block, wrapped in schema that labels what it is.
Yes, because AI answers are built from indexed pages. Every major assistant retrieves from a crawled index, so pages that aren't crawlable, renderable, or structured never enter the candidate pool. Classic SEO is now the entry requirement for AI visibility, and the two programs share almost all of the same work.
Technical recovery and on-page work typically show movement in 30–60 days. AI citation lift on long-tail and comparison queries usually lands in 30–90 days. Category-level authority and head-term rankings are a 6–12 month curve. Every engagement ships a sequenced 90-day plan so early wins fund the long work.
You get a forensic audit, a prioritized 90-day execution plan with effort and impact scoring, and optional done-for-you implementation by our engineers and editors. Pricing is scoped per engagement based on catalog size, locale count, and whether you want execution included. Implement our 90-day plan and if you don't see results in 3–6 months, we refund you in full.
Audits scoped within 24 hours. Results within 90 days, or your money back.
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