Industry · Financial services
AI Visibility for Financial Services Firms.
When a buyer asks ChatGPT, Gemini, Perplexity or Claude: "[advice type] adviser in [city] for [client situation]", is your firm in the answer? For most, the answer is no.
Exclusion rate
90%
of firms in our audit data are not named in the relevant AI answers.
Buyer query shape
"[advice type] adviser in [city] for [client situation]"
Time to first measurable lift
30 days
From baseline to first re-measurement.
The failure pattern.
FCA-regulated firms are conservative with marketing language, often resulting in vague positioning that AI systems cannot use to differentiate. Compliance becomes the alibi for exclusion.
The four levers
How we engineer selection in financial services.
Compliant specificity
Sharpen positioning within FCA boundaries: defined client situations, defined services, defined fee model. Specificity is compliant.
FCA-register signal
Encode FCA permissions and register entries in machine-legible form so AI can verify regulated status.
Independent verification
Construct citation paths through Citywire, Money Marketing and FT Adviser that AI systems can read and weight.
Client-shape definition
Replace 'high-net-worth individuals' with the structured client situations (sale of business, divorce, inheritance) you actually serve.
From the field
Financial services buyers research heavily before contact. AI-assisted research is now mainstream in the under-50 bracket and growing rapidly above it.
Common questions.
Will this conflict with our compliance team?
No. AVO produces sharper, more verifiable, more substantiated positioning. Compliance teams typically welcome it.
Does this apply to wealth managers as well as IFAs?
Yes. Both segments face the same selection problem in AI category answers; the levers are the same.
Find out where you stand.
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