KYC Fraud Patterns in Insurance — 2026 Field Report

Insurance KYC and claims flows touch more document types than almost any other industry — IDs, driver's licenses, vehicle titles, medical reports, police reports, utility bills, and proof of loss photos. That breadth creates a correspondingly broad attack surface. These are the fraud patterns we see most often in 2026.

1. Synthetic IDs with real names

The dominant 2026 pattern: attackers pair a real (scraped) name and address with an AI-generated ID image. The ID looks plausible but fails forensic checks on microprint, ghost portrait, and MRZ checksum.

2. Template-reused medical reports

We increasingly see forged medical reports that reuse a single legitimate template with swapped patient data. The giveaway is hospital header alignment that drifts by a few pixels between versions — a signal human reviewers almost never catch.

3. Backdated utility bills

AI image models now produce utility bills with believable account numbers and usage histories. Forensic checks on typography consistency with the known issuer template catch most of them.

4. Staged proof-of-loss photos

EXIF metadata analysis, JPEG ghost detection, and shadow-consistency checks catch most staged or AI-edited claim photos. This is one area where legacy image forensics still outperforms pure LLM verification.