Original research on how banks, fintech companies, lenders, insurers, and wealth management firms appear across AI search and high-intent financial discovery.
Key findings
The public page is designed for journalists, analysts, newsletters, and industry operators. Findings stay tied to the benchmark sample and collection window.
ChatGPT is highly cautious with financial queries, heavily favoring professional intervention, whereas Gemini is much less likely to suggest seeking expert help.
Direct brand recommendations are relatively rare across the board, but Gemini is the most likely engine to surface specific financial companies or advisors.
AI models rarely prompt users to check for licenses or certifications like CFP or fiduciary status, indicating a blind spot in how they evaluate financial trust.
Claude is the most likely model to discuss fees, minimums, or cost structures, making transparent pricing content a valuable asset for AI visibility.
This benchmark is researched and maintained in-house. For the underlying data, methodology detail, or an on-record comment for your story, reach the research lead directly.
Sector intelligence
Two proprietary datasets, refreshed on a set cadence: curated search-demand intelligence across every financial services service we cover, and a controlled study of how ChatGPT, Claude and Gemini actually advise financial services buyers. Every figure is citable — anchors are stable.
12-month demand trend
| ChatGPT | Claude | Gemini | |
|---|---|---|---|
| Recommends hiring a professional | 65% | 48% | 18% |
| Suggests DIY first | 38% | 20% | 10% |
| Names specific providers | 8% | 15% | 23% |
| Gives price or cost info | 25% | 38% | 28% |
| Tells to check reviews | 8% | 8% | 0% |
| Tells to verify credentials | 5% | 8% | 3% |
| Mentions case studies / portfolio | 0% | 0% | 0% |
| Mentions local proximity | 13% | 13% | 5% |
| Gives selection criteria | 40% | 43% | 23% |
| Warns about red flags | 8% | 15% | 8% |
| Asks a clarifying question | 58% | 65% | 0% |
| Recommends multiple quotes | 20% | 20% | 5% |
The ARI is the average rate at which ChatGPT, Claude and Gemini recommend hiring a professional, per industry. A named, quarterly-tracked index — cite it as “Authority Specialist AI Recommendation Index”.
| 1 | Legal | |
| 2 | Healthcare | |
| 3 | Automotive | |
| 4 | Beauty | |
| 5 | Home Services | |
| 6 | Real Estate | |
| 7 | Financial Services | |
| 8 | Fitness | |
| 9 | Professional Services | |
| 10 | Education | |
| 11 | Manufacturing | |
| 12 | Technology | |
| 13 | Ecommerce | |
| 14 | Hospitality |
About this benchmark
This report measures how visible financial services brands are across AI-generated search and recommendation environments, with attention to mentions, recommendations, citations, source quality, sentiment, trust evidence, and hallucination risk.
Measures whether AI systems recognize brands organically and where they appear inside generated recommendations.
Separates brand-owned websites, directories, media, review platforms, regulatory sources, and uncited assertions.
Checks whether public evidence supports safer descriptions, comparisons, and recommendations in high-intent searches.
AI-visible brands
Rankings are only shown when verified public data exists. The language is intentionally visibility-based, not a claim that one company is objectively better than another.
| 1 | IRS | ||
| 2 | Freddie Mac | ||
| 3 | Vanguard | ||
| 4 | State Farm | ||
| 5 | Fannie Mae | ||
| 6 | Experian | ||
| 7 | TransUnion | ||
| 8 | Equifax | ||
| 9 | Fidelity | ||
| 10 | MassMutual |
Extracted verbatim from 120 stored AI responses (2026-07 edition). Mention frequency in stored AI responses. A mention is not an endorsement.
Methodology
Results are framed as observations from a defined sample and collection window. AI outputs can vary by model version, location, personalization, retrieval mode, and time.
Build a clean industry list covering national brands, mid-market players, organic challengers, specialists, and emerging entities.
Group prompts by recommendation, comparison, trust, alternative, informational, local, and high-value buyer intent.
Collect model outputs with consistent prompt wording, collection dates, country context, and search mode notes where available.
Review brand matches, citation URLs, sensitive claims, hallucination flags, and public wording before publication.
Downloads
Public downloads become active only when the underlying benchmark data and citations are ready for reuse.
Public report formatted for journalists, analysts, and internal stakeholders.
Summary table for verified benchmark metrics and public ranking fields.
Reusable PNG/SVG chart assets with attribution and canonical source links.
Collection window, prompt categories, model setup, scoring rubric, and limitations.
Resources
Service frameworks, authority playbooks, and implementation resources for financial services brands. Expand to see the full library, all reachable directly from this page.
Authority Specialist audits AI mention presence, recommendation gaps, citation sources, competitor visibility, E-E-A-T signals, and the 90-day authority roadmap required to improve visibility.