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Best return-fraud detection tools (2026)

Claimscan

Return-claim photo forensics

Forensic image analysis of damage/return photos to flag manipulation, reuse and AI-generation — a non-accusatory decision aid.

Best for: SMB & D2C sellers who refund or replace on the strength of a photo, without requiring the item back.

Transaction-fraud platforms (Signifyd, Riskified, Forter)

Checkout / payment-fraud prevention

Score and screen orders at purchase and guarantee against payment chargebacks.

Best for: Mid-market and enterprise merchants with significant card-fraud and chargeback exposure.

Returns-management platforms (e.g. Loop)

Returns workflow & exchanges

Run the return portal, automate exchanges and store credit, and manage return logistics.

Best for: Brands optimising the returns experience and reverse logistics rather than verifying claim evidence.

Manual review

Status quo

A support agent eyeballs the claim photo and decides — no specialised tooling.

Best for: Very low claim volumes where a forensic check is not yet worthwhile.

How to choose

If fraudulent orders and chargebacks are your problem, a checkout transaction-fraud platform fits. If your friction is the returns workflow itself, a returns-management platform fits. If your losses come from photo-only refund and replacement claims — increasingly including AI-generated images — that is a forensic-verification problem, which is the gap Claimscan fills.

These categories are complementary, not mutually exclusive: a brand can run checkout fraud prevention and still have no defence against a fabricated post-purchase damage photo.

Keep reading

Frequently asked questions

What is the best tool to detect fake return photos?
Detecting fabricated or AI-generated claim photos is a forensic-imaging task rather than a checkout-fraud task. A photo-forensics tool that layers metadata, provenance, pixel and AI-detection signals is the right category for that specific problem.
Do transaction-fraud platforms catch return fraud?
They focus on fraudulent orders and chargebacks at the point of purchase. Post-purchase claims built on a manipulated damage photo fall outside that scope, which is why the two categories are often used together.
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