Are AI-generated return photos a real threat?

Until recently, faking a damage photo meant editing a real picture — slow, and detectable. Consumer image generators have removed that friction: a short text prompt can produce a photorealistic image of a cracked screen, a stained garment or a dented box on demand. For sellers who replace goods on the basis of a single photo, that lowers the effort needed to file a fraudulent claim.

Generated images differ from camera captures in ways an automated check can measure. A dedicated AI-detection layer evaluates statistical and structural hallmarks of synthetic imagery. Just as tellingly, an AI image arrives without the metadata, sensor-noise pattern and provenance signals a genuine phone photo would carry. Claimscan combines these signals into a manipulation-likelihood report rather than a single verdict, and flags such images as LIKELY_AI_GENERATED for human review.

Build a quick forensic check into the claims workflow before refunding photo-only claims, and treat a LIKELY_AI_GENERATED result as a reason to request additional evidence — a second angle or a short video — not as grounds for an automatic accusation. The aim is to keep the refund process smooth for honest customers while removing the easy win for fabricated claims.