AI Can Fake the Evidence Now, and Refund Fraud Is Getting Easier

A shopper can now generate a flawless receipt, a photo of a damaged product that arrived in perfect condition, and a police report for a parcel that was never lost, all in the time it takes to write the claim. And 65% of shoppers say AI has already made falsely claiming a refund easier, according to Ravelin's State of Refunds 2026 research.

This is the part of the fraud story that should worry retailers most, because it does not just add more fraud. It quietly breaks the thing every refund process has always leaned on: the evidence.

Is AI Really Making Refund Fraud Easier?

Yes, and shoppers themselves say so. In Ravelin's survey of 6,200 shoppers, 65% said AI has made it easier to falsely claim refunds, and 59% agreed that AI "supercharges" refund abuse. This is not a future threat that vendors are warning about. It is a change consumers are already reporting in their own behaviour.

The tooling makes it trivial. Generative AI can produce a receipt that mirrors a real one down to the logo, the item list, the timestamp and the transaction number, and it can fabricate a convincing image of a damaged product that arrived intact. The claim arrives looking exactly like a legitimate one. On the merchant side, 46% already say they are concerned about AI being weaponised for fraud. The concern is warranted, and the fakes only get better from here.

Why Doesn't Checking the Evidence Harder Fix It?

Because it is an arms race the retailer cannot win one document at a time. Every new check a claims team adds, the fraudster's tools quickly learn to pass, and the fraudster only has to get through a busy review process once. Tightening evidence standards mostly slows down honest customers while the fabricated claims sail through looking perfect.

That is the trap. The whole refund process was built on the assumption that a receipt, a photo or a report is proof of something. Once those can be generated on demand, the artifact stops being evidence and becomes just another thing on the screen. Asking for more of it, or scrutinising it harder, is asking the wrong question.

What Can You Still Trust When the Proof Is Fake?

Behaviour, because a pattern is far harder to fake than a document. One fabricated receipt is convincing in isolation. What AI cannot easily manufacture is a clean history: a claimant who files the same "item not received" or "arrived damaged" claim across many different retailers is describing themselves, no matter how perfect each individual piece of evidence looks.

That is the signal that survives the fakes. A single claim can be dressed up flawlessly. A repeated pattern across the network cannot, because the fraudster does not control what every other retailer has seen. The document lies easily. The behaviour does not. We wrote about why that repeat pattern stays invisible to any single retailer in The Serial Returner No Single Shop Can See.

How Does That Actually Stop It?

By deciding on the claimant, not just the claim. When a retailer can see whether this person behaves like this everywhere, a beautifully faked receipt stops being the deciding factor. The genuine customer with a real problem looks nothing like the account working the same claim across a dozen brands, whatever their paperwork says.

That also protects the honest customer, who is otherwise the main casualty of the arms race. Instead of putting every claim through heavier and heavier evidence checks to catch the fakes, a retailer can wave through the many and look closely at the few whose behaviour, not whose documents, stands out. We describe what that changes for a claims team in Fewer False Positives, Faster Claims, and how it applies when the proof itself lives with the carrier in The Carrier Knows What Happened to Your Parcel.

The Evidence Was Never the Point

For years, fighting refund fraud meant getting better at examining evidence. AI has quietly ended that era. When the receipt, the photo and the report can all be generated to order, the document is no longer where the truth lives.

The retailers who struggle will be the ones still trying to out-verify the fakes. The ones who cope will be the ones who stop asking "is this document real?" and start asking "does this person do this everywhere?" That is a question AI cannot answer for the fraudster, because the fraudster does not get to write everyone else's records.