Case study
Fraud detection
AI-powered customer service agents.
Digital marketing
Customer service
24/7 supportChallenge
An automobile insurance company faced rising losses due to fraudulent claims that were difficult to detect using traditional rule-based systems. Manual investigations were time-consuming, and the client needed an intelligent, scalable way to identify suspicious patterns early in the claim process.
Solution
We developed a targeted AI model trained on historical claims data, combining structured inputs with contextual indicators to flag anomalies. The model uses pattern recognition and classification techniques to score each claim for fraud risk in real time, enabling rapid triage and investigation while minimizing false positives.
Impact
The AI solution reduced claim review time by over 50% and helped identify fraudulent cases with significantly higher accuracy. This led to substantial cost savings, faster settlements for legitimate claims, and a more robust fraud prevention strategy across the client’s operations.
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