Document fraud in insurance claims
Claim photos were the first wave. Now it is the documents: receipts for items never bought, medical certificates with moved dates and invoices for repairs that never happened. Here is what it looks like from the investigator's chair.
Updated 2026-08-31 · Veriflied
Typical cases
Theft and burglary
Receipts for valuable items produced after the theft. The catch: the document's file was created after the claim, or years after the claimed purchase. Photos of the item taken after the theft date are another classic finding.
Travel and illness
Medical certificates and record printouts with an edited date or diagnosis so the treatment falls within the trip or the cover.
Property and contents
Contractor invoices for repairs never carried out, often from a real company with a wrong account number. Damage photos AI-edited to make the damage look larger.
Motor
Workshop invoices from template generators and damage photos taken before the reported incident.
Why the eye is not enough
The documents look right because they were made to look right. And the handler typically has minutes, not hours. What separates a fabricated invoice from a genuine one sits inside the file: which program made it, when, whether it was edited, and whether that fits the case's own dates. Nobody can see that information, but a program reads it in seconds.
What a forensic analysis adds
For every document: producer chain (issued by a billing system or made with a generic tool?), timestamps cross-checked against incident date, claim date and purchase date, editing history and recovery of earlier versions, and for images an AI detector with heatmap. Findings are grouped into named patterns with explanations, and the report includes the concrete questions the investigator should put to the claimant.
The report is built for the case, not for an algorithm: hash, timeline, findings per layer and the extracted original document where one exists. It is material that can be used onward, not just a score.
Where it fits in the flow
Most insurers already have rule engines and indicator lists at case level. Document and image forensics is the layer underneath: it determines what actually happened to the submitted files, and it can run automatically via API on every document above an amount threshold, or manually in the platform on the cases the investigation unit is handling. All processing takes place in the EU.
Frequently asked questions
How many documents are fake?
Nobody knows precisely, because most are never detected. That number only appears once a portfolio of historical cases is scanned systematically. It is one of the things a pilot should do.
Does it replace our existing fraud system?
No. Rule engines work at case level and keep doing so. Forensics adds a layer rules cannot: an assessment of the files themselves.
Can the result be used in court?
The report documents what the file itself contains, with timeline, hash and extracted versions. It is technical documentation. The legal assessment remains human.
How do we get started?
With a closed evaluation on your own material: a selection of historical cases, ideally including known fraud, processed in the EU under NDA. Then the numbers are your own.
Try it on your own document
Create an account and analyse your first 10 images or documents for free. You get a report with the concrete findings, not just a score. All processing in the EU.