Spot questionable claims before the money leaves
We check submitted damage, warranty and complaint claims against your own data. The system prioritises, your people decide.
Most claims are legitimate. The effort belongs to the few that are not.
The same damage is submitted more than once, through different channels, at different times or via different subsidiaries.
Evidence photos are edited or lifted from another case, and cost estimates are visibly inflated.
Incidents are invented or predate the start of cover, which is almost impossible to see case by case.
Matching against your history
- Comparison with earlier cases covering the same damage, the same asset and the same submitter
- Detection of reused receipts and invoices across cases
- Pattern analysis across submitters, repair shops, service providers and addresses
Evidence and images
- Image analysis of submitted photos for metadata, reuse and editing traces
- Plausibility checks on cost estimates against the reported damage and its scope
- Detection of altered documents and inconsistent chains of evidence
Contract and timeline
- Cross-checking incident date, start of cover, warranty period and reporting date
- Consistency checks against location, weather conditions and documented prior damage
- A prioritised case list with reasoning, so your handlers know where to follow up
The few questionable cases become visible while the rest pass without extra friction.
Every flag comes with concrete evidence, not just a score.
Human final decisions and documented steps, in line with Article 22 GDPR.
Claims review
Who is this service for?
For companies that handle damage, warranty or complaint claims themselves: manufacturers, retailers, trades businesses, landlords and insurance intermediaries. CAVRIX is not an insurer and does not act as one.
Does the system decide on rejection or payout?
No. Article 22 GDPR limits fully automated decisions with legal effect. The system therefore only prioritises and presents findings with reasoning. The decision is always made by a person on your side.
Is this kind of screening lawful under data protection rules?
Recital 47 GDPR explicitly names fraud prevention as a legitimate interest. Lawful does not mean unlimited: you need purpose limitation, data minimisation, a documented balancing test and deletion periods. We set exactly that up with you.
What happens to the images in a claim?
They go through the same image review as in our deepfake detection module: metadata, reverse search, consistency with location, time and weather. A detector score on its own is not proof to us, and we do not present it as such.
How do you handle false positives?
Every flag is shown with its source so your handlers can dismiss it in seconds. Feedback from their work flows back into the rules, so the same false flag does not keep generating work.
Let us look at your claims process
Write to info@cavrix.de and tell us what claims reach you and how they are handled today. We will show you where screening genuinely pays off.