Return Fraud Image Shield

Build a defensive program against AI-generated and recycled damage photos in online returns, combining metadata rules, image-authenticity signals, behavioral scoring, and computer-vision comparison against the catalog. Output is a per-claim decisioning rubric, an evidence checklist for chargeback representment, a reviewer SOP, and a KPI scorecard — tuned for a retailer who is seeing photo-based not-as-described or damaged-on-arrival claims climb faster than their return volume can explain.