Insurer Saves $12M Annually by Detecting Fraudulent Claims with AI
Deploying an AI fraud detection platform that catches suspicious patterns across motor, health, and travel claims before payout.
Project Overview
The Challenge
Fraud was estimated at 8–12% of paid claims, but the existing rules engine missed sophisticated organized fraud rings.
- 1Limited visibility into cross-line and cross-product fraud patterns
- 2High investigator workload with low conviction rates on flagged cases
- 3Inability to detect collusion between claimants, providers, and adjusters
Our Solution
CloudGate built an AI fraud detection platform combining anomaly detection, network analytics, and natural language processing of claim narratives.
- Graph-based network analytics identifying organized fraud rings
- NLP analysis of FNOL narratives for inconsistency detection
- Investigator workspace prioritizing highest-value cases
The Results
- Dismantled three organized fraud rings within the first year
Technologies Used
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