What AI says about your financial brand matters
Customers ask AI which bank to trust and which policy to buy. Track those answers weekly across 5 models, monitor sentiment, and keep a dated archive of every claim AI makes about your products.
What AI told savers and policyholders, on record
Views built for banks, insurers and fintechs that treat a misquoted rate as a compliance matter.
Answer Archive
When a model misquotes your rate, prove it
A prospect who reads a wrong APR in an AI answer never calls to double-check. Each weekly run stores the full response with your brand highlighted, so a claim about fees, rates or coverage arrives with its exact wording, model and date. Compliance reviews evidence rather than a customer's screenshot.
- Exact wording on rates, fees and coverage
- Dated per model, ready for review
- Escalations backed by the archived answer
Share of Voice
Who wins "best savings account" this week
Comparison prompts decide where deposits and policies go, and incumbents, challengers and comparison sites all compete for the same answer. Your share sits against every provider you track, refreshed weekly instead of at the pace of a quarterly brand study. When a challenger gains, the cited domains below show whether a comparison site or a news story is doing the work.
- Share per bank, insurer and fintech tracked
- Weekly reads between quarterly brand studies
- Comparison sites driving each rival's gains
BI Reporting
AI visibility in the decks your committees read
Risk and marketing committees do not log into new tools. The Looker Studio connector feeds the same weekly numbers into the dashboards they already review, with Power BI and the API covering the rest of your reporting stack. When someone asks where a figure came from, the dated archive answers.
- Weekly numbers straight into committee dashboards
- Looker Studio, Power BI and API access
- Every figure traceable to a dated answer
Why Financial Brands Choose LLM Pulse
High-stakes financial questions now go to AI first, and the answers decide who earns trust.
Win Product Comparison Prompts
Track prompts like "best savings account" or "cheapest home insurance" weekly and see which providers AI names first.
Monitor Trust and Safety Queries
Prospects ask AI whether a provider is safe before they sign up. See exactly how those answers describe you.
Keep Every Answer on Record
Full answer text is stored with each weekly run, so your team can review what AI claimed about rates and products, and when.
Spot Wrong Rate and Product Claims
Read the exact wording AI uses about your fees and coverage, and trace each claim to the source it cites.
Benchmark Against Banks and Fintechs
Share of voice shows whether AI recommends you, an incumbent or a challenger on the prompts that matter.
Track Sentiment Over Time
A sentiment score on every mention shows how the tone about your brand moves, week by week.
How It Works
A sober, repeatable process for a regulated industry.
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1
Map your product and trust prompts
Add comparison prompts for each product line plus the trust questions prospects ask. Prompt research finds the ones you missed.
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2
Track answers weekly across 5 AI models
Each run stores the full answer text, mention positions and a sentiment score per mention.
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3
Review claims and sources
Compare what each model says about your rates and products with what is true, and trace wrong claims to the cited pages.
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4
Correct the record
Update your own pages, direct outreach at third-party sources, and confirm the change in the next weekly run.
Built for Financial Use Cases
Where financial services teams put LLM Pulse to work.
Banks and challengers
Track "best bank for" prompts across your markets and see who AI names first.
Insurers
Monitor policy comparison prompts and how AI describes your coverage and claims process.
Fintech apps
See whether AI recommends your app on category prompts and which reviews it cites.
Lending and credit
Follow how AI answers rate and eligibility questions where an outdated number costs applications.
"After noticing rising visits from various LLMs in GA4, we needed visibility into those black boxes: which models were mentioning us, in which answers, and how that was changing over time. LLM Pulse gave us the clarity to understand our brand's evolution across AI models and to shape new strategies to boost our exposure."
Frequently Asked Questions
Common questions from banking, fintech and insurance teams.
Explore the features behind this solution
Go deeper on AI search
AI Search Data Studies
Research on how AI models handle high-stakes recommendation questions.
Read moreReputation Analysis
How LLM Pulse summarizes the way AI frames your brand's strengths and risks.
Read moreFree AI Visibility Report
Get a first snapshot of how AI models describe your financial brand.
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