AI Fraud Surge Forces Retailers to Rethink Return Policies

Retailers are facing a new wave of refund fraud driven by generative AI. Data from fraud prevention platform Forter shows that AI-generated damage claims are now the fastest-growing form of return abuse. Shoppers and organised crime groups are using generative AI to create convincing fake photos, videos, and documents that make undamaged goods appear defective.

The simple read is that fraud rates are rising. The better read is that this changes the economics of e-commerce returns and creates a structural wedge between retailers that can detect synthetic damage claims and those that cannot. Return abuse already costs U.S. retailers an estimated $100 billion annually, and AI-generated claims accelerate that trend without a proportional increase in manual detection capacity.

Generative AI Fraud and the Return Policy Dilemma

Generative AI lowers the skill barrier for fraud. A shopper no longer needs a damaged product or a real photograph. A single prompt can produce a realistic image of a torn seam, a cracked screen, or a stained garment. The same technology can generate fake shipping labels, altered receipts, and fabricated correspondence with customer service.

Retailers face a choice. Tighten return policies and risk losing legitimate customers who value hassle-free returns. Or invest in AI-powered fraud detection that can distinguish synthetic images from real damage. The latter requires capital, data science talent, and integration with existing order management systems. Smaller retailers without those resources are most exposed.

The read-through to fraud prevention vendors is direct. Forter and similar platforms should see increased demand as retailers seek to automate the verification of damage claims. The same dynamic applies to payment processors that underwrite chargebacks. If fraud rates climb, processors may raise fees or tighten terms for merchants with high return volumes.

Valuation and Catalyst Path for Retailers

Return rates are a hidden margin driver. A retailer with a 10% return rate and a 30% gross margin loses three percentage points of gross profit to returns before accounting for shipping and restocking costs. AI-generated fraud adds to that drag without generating any offsetting revenue.