The Data

How financial brands actually score on AI visibility

Most financial institution websites are not ready for AI-driven discovery. This page is the living source for the Atlas Instinct audit dataset: every figure is a measurement, not a projection, and the numbers update as the dataset grows.

Updated July 2026 · 420 audits · 181 financial institution and brand websites

60/100Average overall score (range 10 to 88)
23%Score below 50: effectively invisible to AI answer engines
16%Pass high-reliability audit standards
43%Score below 60 overall

Where sites fall down, by category

Average score across all 420 audits, as of July 2026:

Accessibility: 51The weakest category; 43% of sites are failing it
SEO: 53
Reputation: 58
GEO / AEO: 58
Technical: 63The strongest category

Accessibility is the number one gap. That matters for AI because the same structure that helps assistive technology, clean semantic markup, labels, and logical hierarchy, also helps machines parse and quote your content.

The fixes that come up most

The most frequently prescribed improvements across the dataset, in order:

  1. Implement structured data (schema): recommended for 85 sites. The single most common fix, and the highest-leverage move for AI visibility. Schema tells AI systems exactly who you are, what you offer, and how your content is organized.
  2. Implement lazy loading: 51 sites
  3. Add ARIA labels: 38 sites
  4. Claim and optimize review profiles: 37 sites
  5. Add a viewport meta tag: 28 sites
  6. Add form labels: 24 sites
  7. Set canonical URLs: 23 sites

What this means for financial brands

Customers increasingly ask an AI assistant before they open a search engine. If your site is in the bottom quartile for AI discoverability, you are not in the running when someone asks an assistant to recommend a bank, credit union, or provider. The good news is that the highest-impact fixes, structured data, accessibility, and clean technical hygiene, are well understood and achievable. The brands that treat AI visibility as a discipline now, the way they treated SEO fifteen years ago, will own the recommendations their competitors never see.

See where your site stands

Two minutes, ten questions, no form: the AI Recommendation Test estimates whether AI assistants would recommend your institution.

Take the test Get a full audit

Methodology

These benchmarks come from AI visibility audits run through the Atlas Instinct platform, which evaluates each site across GEO/AEO, SEO, accessibility, technical performance, and reputation. The dataset grows as new audits run, and this page updates with it. To cite these numbers, reference this page with its as-of date. For the story behind the data, read Famous and Invisible.

Changelog

  • July 2026: Dataset grew from 404 audits of 176 sites to 420 audits of 181 sites. Average overall score moved from 58 to 60. High-reliability pass rate moved from 17% to 16%. Structured data recommendations moved from 83 to 85 sites.
  • May 2026: First public release of the benchmarks: 404 audits across 176 sites.
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