AI
INSURANCE FRAUD
IDENTIFICATION
Fraud Detection You Can Trust
AI
INSURANCE FRAUD
IDENTIFICATION
Fraud Detection You Can Trust
DAFNE is an artificial intelligence platform that analyzes damage in accident images to detect large-scale fraud.
How it works
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Frauds that don't look like frauds
The problem is in the images
Many fraudulent claims aren’t invented, but recycled: pre-existing damage, reused photos, components swapped over time. At first glance, they appear legitimate. The clue, however, is hidden in the images.
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Without history, context is missing
A single accident doesn't tell the whole story.
Fraud emerges only when damage is compared to what has already happened. Without a searchable history, recurrences remain invisible and manual analysis doesn’t scale.
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Damage as a key element
That's where the information is hidden.
In accident images, the most reliable data is the damage itself: shape, location, and visual consistency. This is where reuses, repetitions, and real inconsistencies can be identified.
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DAFNE's approach
Damage analysis, pixel by pixel
DAFNE analyzes accident images by focusing on the damage, without relying on metadata. It automatically identifies the damaged area and describes its visual characteristics in an objective and comparable manner.
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The historian as a comparison
Recurrences emerge automatically
The damage is compared with images already present in the company’s archives. DAFNE identifies reused photos, pre-existing damage, recurring portions, and inconsistencies between claims, even those spanning multiple time periods.
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Reliable, ready-to-use evidence
From AI to decision making
Reports are validated by expert operators and transformed into clear reports, with visual feedback and verifiable references. This output is designed to support operational anti-fraud decisions, not just analysis.
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Advantages
Operational reliability
Only verified evidence, less noise
DAFNE integrates a human-in-the-loop process that validates the results of automatic analysis. Each report is verified by expert operators before being delivered. This ensures maximum operational reliability: fewer false positives, fewer insignificant alerts, and a reduced workload for anti-fraud teams, who can focus only on cases with solid and truly relevant evidence.
Real scalability of anti-fraud
From the sample to the total number of claims
DAFNE is designed to operate on large volumes. Anti-fraud is no longer limited to a small percentage of “suspicious” claims, but can be systematically extended to the entire portfolio. This reduces overall risk and ensures consistent and continuous monitoring over time.
Evidence, not just alerts
Objective and actionable reports
DAFNE doesn’t just generate a score or alert for investigation. It produces a report with a direct comparison of damages, clear and accessible even to non-technical specialists. This provides visual evidence, traceable and usable in internal processes and, when necessary, even in formal or litigation contexts.
