An AI auditor engine for catching claims errors before payout
Client: A US auto and property insurance claims operation
The challenge
The same claims operation was manually spot-checking only a small percentage of estimates and payouts for errors and irregularities, catching a fraction of the mistakes slipping through a high-volume claims pipeline.
Our approach
We built an AI auditor engine that reviews estimates and claim files against historical patterns and policy rules, flagging outliers and inconsistencies for human review before payout, instead of relying on random sampling.
- Moved from spot-checking a small sample of claims to reviewing effectively all of them
- Surfaced irregular patterns that manual sampling had been missing
- Gave the audit team a prioritized queue instead of a random sample to work through
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