AI SEO Statistics: Financial Services (2026-07 edition)

Reading the 120 answers model by model shows how differently the three assistants treat the same financial services questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 65% (ChatGPT) down to 17.5% (Gemini), a 48-point gap on an identical question set.

Across the 40 financial services answers it produced, ChatGPT recommended hiring a professional in 65% of them and suggested a DIY approach first 37.5% of the time. It named a specific provider in 7.5% of answers (about 0.1 distinct providers per answer) and included price or cost information 25% of the time. ChatGPT asked a clarifying question before answering in 57.5% of cases, warned about red flags or scams in 7.5%, and told the buyer to verify credentials in 5%, averaging 581 words per answer. On the remaining cues it told the buyer to check reviews in 7.5%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 12.5%; a selection-criteria checklist appeared in 40% of its answers and a recommendation to gather multiple quotes in 20%.

Across the 40 financial services answers it produced, Claude recommended hiring a professional in 47.5% of them and suggested a DIY approach first 20% of the time. It named a specific provider in 15% of answers (about 0.6 distinct providers per answer) and included price or cost information 37.5% of the time. Claude asked a clarifying question before answering in 65% of cases, warned about red flags or scams in 15%, and told the buyer to verify credentials in 7.5%, averaging 316 words per answer. On the remaining cues it told the buyer to check reviews in 7.5%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 12.5%; a selection-criteria checklist appeared in 42.5% of its answers and a recommendation to gather multiple quotes in 20%.

Across the 40 financial services answers it produced, Gemini recommended hiring a professional in 17.5% of them and suggested a DIY approach first 10% of the time. It named a specific provider in 22.5% of answers (about 0.9 distinct providers per answer) and included price or cost information 27.5% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 7.5%, and told the buyer to verify credentials in 2.5%, averaging 249 words per answer. On the remaining cues it told the buyer to check reviews in 0%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 5%; a selection-criteria checklist appeared in 22.5% of its answers and a recommendation to gather multiple quotes in 5%.

Taken together, ChatGPT is the assistant most likely to route a financial services buyer to a professional (65%) and Gemini the least (17.5%). ChatGPT produced the longest answers, at 581 words on average. Specific providers were named most often by Gemini (22.5%) — even there, roughly one answer in 4 carried a name.

On other behaviors the three models move almost in lockstep — the points of near-consensus for financial services, where all three landed within a few points of each other:

• Mentions case studies or portfolio: 0% across all three models.
• Tells the buyer to verify credentials: 2.5%–7.5% across all three (a 5-point spread).
• Tells the buyer to check reviews: 0%–7.5% across all three (a 8-point spread).
• Mentions local proximity: 5%–12.5% across all three (a 8-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "mentions case studies or portfolio" (identical coding in 100% of questions) and least consistently on "asks a clarifying question" (15%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the financial services buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 5% of answers on average. Verifying credentials or certifications appeared in 5%. Warning about red flags or scams appeared in 10%.

On structuring the decision, a selection-criteria checklist showed up in 35% of answers on average and a recommendation to gather multiple quotes in 15%. The single least-reproduced protective signal for financial services is "tells the buyer to check reviews" at 5% on average — the clearest opening for content that supplies it, since the models are not yet reliably surfacing that guidance on their own.

The 40 questions behind every percentage on this page were drawn from real financial services (accountants, advisors, insurance, mortgage) buyer journeys, expanded from 4 seed prompts. Each was put to all 3 models once, with identical wording, so the rates above describe how the assistants handled this exact financial services question set — not a general prior or a hand-picked subset. The full list is shown earlier on this page; the coded percentages are what those specific questions produced.