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
- Claims
- SX-2026-04871
- Date
- 14/03/2026
- Vehicle
- Alfa Romeo Stelvio
01 / 06
Ingestion of the claims
Every day the company sends claims to be verified according to its operational criteria: value, geographic area, sampling, and alerts.
02 / 06
Automatic anonymization
The images are stripped of sensitive elements—license plates and faces. DAFNE is interested in the damage, not the identity.
- Type
- Broken Glass
- Extension
- 0.31 m²
- Signature
- 8F2A·4C19
03 / 06
Damage analysis
DAFNE identifies and isolates the damage, analyses its shape, extent and typology, and constructs a technical representation comparable over time.
04 / 06
Matching with the historical
The damage is compared with the company’s archive to reveal recurrences and reuses between claims even distant in time.
- Claim
- SX-2025-03562
- Date
- 12/01/2025
- Vehicle
- Alfa Romeo Stelvio
Match confirmed by M. Rossi
05 / 06
Human validation
High-confidence matches are verified by specialized analysts: false positives are eliminated and the case is confirmed. Human intervention is focused only where necessary.
06 / 06
Report generation
If confirmed, a structured evidence report is produced, with a direct comparison between the damage and traceable references.
Four levels of analysis
Every claims leaves traces. Not only in the declared dynamics, but also in the image pixels, file metadata, and attached documents. DAFNE reads them, correlates them, and compares them with historical records. The four levels do not operate in isolation: the evidence cross-references and reinforces each other. No result is sent to the insurance company until validated by an expert operator.
Pixel Analysis
From fraud to risk
Behind an image lies information the naked eye can’t see: when it was taken, the device used, and whether it has been altered. DAFNE detects discrepancies between the date of the shot and the date of the accident, traces of editing, images generated or retouched using artificial intelligence, and inconsistencies within the metadata chain.
Metadata Analysis
Each file tells how it was born.
Behind an image lies information the naked eye can’t see: when it was taken, the device used, and whether it has been altered. DAFNE detects discrepancies between the date of the shot and the date of the accident, traces of editing, images generated or retouched using artificial intelligence, and inconsistencies within the metadata chain.
Document Analysis
The paper also has cracks.
Estimates, invoices, forms, and appraisals can contain anomalies that are difficult to manually detect. DAFNE detects changed headers, fictitious names and contact details, recurring phone numbers in seemingly unrelated cases, and reused documents with minor variations from one claim to the next.
Satellite image analysis
The claim in its context.
Thanks to the partnership with LambdAI Space, the analysis can extend beyond the vehicle to include buildings, roofs, and outdoor areas. This is a particularly useful tool in property management, where photographic documentation is often partial and acquired only after the event.
The Visada Ecosystem
Clients
Partner
Investors and Financing
Awards and recognitions
Explore DAFNE
Book a demo to see DAFNE in action
Find out how DAFNE analyzes claims, identifies anomalies, and provides validated evidence that can be directly used by anti-fraud teams. Enter your email address: our team will contact you to arrange a dedicated demonstration.