AI Retail Returns Photo Verification

Stop refunding boxes of bricks, worn clothes, and missing accessories. AI-verified return photos confirm condition and contents before the refund posts.

44%
Drop in fraudulent refund value
<400ms
On-device verification
+18 pts
Profit margin protection
$0.008
Per verification
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Return Fraud Is Eating Retail Margin

Common challenges teams face without automated verification

Wardrobing

Customer wears the item once, returns it for full refund. Without condition verification, retailers eat the loss and the item often can't be resold.

Empty-Box Refunds

Returned packages arrive with a brick, a different product, or nothing at all. By the time the warehouse opens it, the refund has already posted.

Missing Accessories

Customer keeps the charger, cable, or accessory and returns the main item. Refunds get issued without checking what's actually in the box.

Slow Warehouse Triage

Warehouse teams open every return, inspect by hand, and route. The cost per return inspection often exceeds the margin on the item.

Policy Inconsistency

Different return-portal vendors apply different standards. Customers learn to game whichever path is most lenient.

How It Works

1

Customer Captures Return Photo

In the return portal or app, the customer is asked to photograph the item before shipping. VerifyAI's SDK guides them to a clean, on-axis frame.

2

On-Device Verification

AI confirms the photographed item matches the original SKU, all included accessories are visible, and visible condition meets the return policy.

3

Decision at Capture

If the photo passes, the return label is issued and the customer ships. If it fails (wrong item, visible damage, missing parts), the policy decision is communicated immediately.

4

Warehouse Reconciliation

When the return arrives, the warehouse opens it and compares against the AI-verified pre-shipment photo. Discrepancies (different item, fewer accessories) trigger an automated dispute.

Key Features

SKU Match Detection

AI confirms the photographed product matches the SKU the customer is returning — same item, same color, same size where visible.

Accessory Completeness Check

Verifies all expected accessories (chargers, cables, manuals, original tags) are visible in the return photo before label issuance.

Condition Scoring

Identifies obvious worn condition, stains, missing tags, and damage. Customers returning visibly used items get policy-appropriate decisions.

Anti-Fraud Signals

Detects re-used return photos, screen captures, and stock-image submissions. Repeat offenders surface to risk review.

Return-Portal Integration

Pre-built integrations with Loop, Happy Returns, Returnly, Narvar, and Shopify Returns. Plus REST API for custom return stacks.

Warehouse Reconciliation

Compares incoming return contents to the pre-shipment AI-verified photo. Mismatches trigger refund hold and customer follow-up.

Measurable Impact

44%
Fraud Refund Reduction

Drop in fraudulent refund dollars

-31%
Wardrobing Returns

Items returned in visibly worn condition

-22%
Warehouse Triage Time

Faster reconciliation with pre-shipment evidence

$0.008
Per Verification

Inclusive of AI analysis and storage

Frequently Asked Questions

Protect Margin From Return Fraud

Verify every refund-eligible return with AI before the label is issued. Start your free sandbox today.

Get in Touch

Questions about pricing, integrations, or custom deployments? We'd love to hear from you.