Sector guide
Financial services
Typical uses: Credit decisions, Fraud detection, Anti-money laundering, Customer service, Advice.
For reference purposes only. Not legal advice.
Who this is for: teams in financial services that build or buy AI.
Overview
Financial firms use AI where errors are costly and affect people directly: who gets credit, which transactions are flagged, what advice a customer receives. Regulators already supervise these activities, so AI is usually judged against existing fairness, conduct and model risk expectations as well as any AI-specific law.
Region pointers
Credit scoring and certain insurance uses are high-risk under the EU AI Act (Annex III), with duties from 2 Dec 2027. European Union page
Fair lending and consumer reporting rules continue to apply to AI-assisted decisions. United States page
FCA expectations and the Consumer Duty apply to firms using AI. United Kingdom page
RBI's FREE-AI framework and SEBI proposals set expectations for regulated entities (status to be checked). India page
What to do now
Questions to ask
- Which of our models decide or strongly influence access to credit or insurance?
- Can we show approval and error rates by group, and who reviews them?
- How does a customer ask for a human review of an automated decision?
- Who approved each model, and when is it next revalidated?
- What do we do when a vendor changes a model we rely on?
Common mistakes
- Treating a vendor score as someone else's problem.
- Testing only overall accuracy.
- No route for applicants to contest.
Related tools
Reviewed 3 Oct 2026. Sources: European Commission: AI Act overview.
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