Insurance KYC and claims touch more document types than almost any other industry: IDs, driver's licenses, vehicle titles, medical reports, police reports, utility bills, proof-of-loss photos. The attack surface is huge. Here are the patterns we see most 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
Forged medical reports that reuse one legitimate template with swapped patient data. The giveaway: hospital header alignment drifts by a few pixels between versions. Human reviewers almost never catch it.
3. Backdated utility bills
AI image models now produce utility bills with believable account numbers and usage histories. Typography consistency checks against 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 beats pure LLM verification.