Fairness testing, actuarial validation and conduct supervision
Insurance
Underwriting and claims decisions are the most closely watched AI applications in insurance, because the harm from an unfair model is individual, documented and litigable. We evidence fairness testing and actuarial review rather than asserting them, and keep a reviewable trail behind every customer-affecting decision.
Pressures
What shapes delivery in this sector.
Fairness testing
Proxy discrimination must be tested for and evidenced, not asserted.
Actuarial validation
Models influencing pricing or reserving need actuarial review alongside technical validation.
Conduct supervision
Distribution and claims handling remain subject to fair-treatment obligations regardless of automation.
Use cases
Where value shows up first.
- Submission intake, document extraction and risk-flagging
- Claims triage and fraud-signal prioritization
- Policy wording comparison and endorsement drafting
- Complaint-handling summarization with audit trail
Evidence
What we leave behind.
- Fairness test plan and results by protected characteristic proxy
- Actuarial sign-off memo for pricing-adjacent models
- Customer-facing explanation templates approved by compliance
Next step
Discuss an insurance use case.
A confidential discovery call with your risk, compliance and technology leadership.