Fraud Detection Agent with Complete Audit Trail
Specialty lines insurer, Southwest US
01 / Challenge
The SIU (Special Investigations Unit) of 8 investigators was reviewing 400 claims monthly for fraud indicators — a purely manual process based on adjuster referrals. Internal audit estimated the company was paying $8–12M annually in fraudulent claims that never reached SIU review. Regulators required that any automated fraud scoring system produce a documented rationale for every referral.
02 / Approach
We deployed a two-stage fraud detection system: a pattern recognition layer that scores every claim at intake using behavioral, network, and historical signals, followed by an evidence synthesis agent that generates a documented fraud referral memo for high-score claims. Every referral includes the specific signals that triggered it — satisfying regulatory auditability requirements.
03 / Outcome
SIU referral volume increased from 400 to 890 per month while investigator headcount remained flat — the additional referrals were higher quality cases from the automated scoring. Confirmed fraud payments identified and denied in the first year totaled $6.8M. Regulatory examination of the fraud detection program found the audit trail to be exemplary.
Representative case study illustrating common agentic-AI deployment patterns in Insurance; not a specific QuettaMinds client engagement.
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