The 2026 Guide to Synthetic Refund Fraud
Synthetic Fraud is the fastest growing vector in e-commerce risk. Learn the 4 types of synthetic scams and how to immunize your return policy.
Definition
Synthetic Fraud: Using generative AI (Midjourney, DALL-E 3, Stable Diffusion) to fabricate damage/loss evidence for fraudulent refunds.
The 4 Attack Types
1. Damage Hallucination
AI-generated damage photos of undamaged items. Customer keeps product and receives refund.
2. Fake Label Generation
AI-created defective shipping labels to bypass return requirements.
3. Missing Item Manipulation
AI object removal from bundle photos to claim missing components.
4. Document Forgery
LLM-generated police reports or medical notes for "stolen packages" or "allergic reactions."
Why Traditional Fraud Tools Fail
Payment fraud tools (Signifyd, Riskified) detect stolen cards via IP/velocity/device analysis. Synthetic fraud uses legitimate customers with valid cards and real addresses—exploiting post-purchase trust.
Defense Strategy
- Require high-resolution photos: Eliminate blurry submissions
- Audit auto-refund thresholds: Sub-$50 auto-approvals are primary targets
- Deploy forensic scanning: Veto detects diffusion artifacts in submitted images
Signal deterrence to fraud communities. Hard targets get skipped.