Generali France uses AI to detect property and casualty insurance fraud
Generali France· FranceShift Technology Force
Generali France extended its partnership with Shift Technology from auto insurance into property damage insurance, deploying Shift's Force solution to detect anomalies in claims in real time by combining internal claims/contracts data with third-party sources (government data, aerial imagery, geolocation). Shift's detection focuses on 107,000 of Generali's 125,000 annual P&C claims, with roughly 3,000 claims analyzed a day and a goal of raising the recognized-fraud rate from 0.7% toward the market-leading 2% benchmark.
Overview
Generali France extended its partnership with Shift Technology from auto insurance into property damage insurance, deploying Shift's Force solution to detect anomalies in claims in real time by combining internal claims/contracts data with third-party sources (government data, aerial imagery, geolocation). Shift's detection focuses on 107,000 of Generali's 125,000 annual P&C claims, with roughly 3,000 claims analyzed a day and a goal of raising the recognized-fraud rate from 0.7% toward the market-leading 2% benchmark.
The challenge
Generali France wanted to improve detection of property and casualty insurance fraud, aiming to raise its recognized-fraud rate beyond 0.7% (versus a market-leading benchmark of 2%) by detecting anomalies in claims files in real time.
The solution
Building on an existing auto-insurance partnership, Generali France extended its use of Shift Technology's Force solution into property damage insurance. Force combines internal data (claims, contracts, sample copies) with third-party data (government data, web/Google, aerial imagery via Google Maps, geolocation) to cross-reference thousands of variables and flag anomalies as soon as a claim is filed, generating a suspicion score and supporting indications for administrators to review.
Reported business value
Shift's detection focuses on 107,000 of Generali's 125,000 annual P&C claims. With Force, around 3,000 claims were expected to be analyzed a day (up from about 300/day previously), with the goal of raising the recognized-fraud rate from 0.7% toward the market-leading 2% benchmark; the automation was also expected to speed up claims processing for both insured and insurer.
Sources
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This record was researched and written with AI assistance, and its claims were checked against the sources above. (EU AI Act art. 50 transparency notice.)
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