With SAS®Detection and Investigation for Insurance, you don't have to accept claims fraud as a cost of doing business.
Detect more fraudulent activity.
Identify suspicious activity, uncover hidden relationships and detect subtle patterns of behavior at every stage of the claims process. Our insurance fraud analytics engine uses multiple techniques (automated business rules, embedded AI and machine learning methods, text mining, anomaly detection and network link analysis) to automatically score millions of claims records in real time or in batch. Customized anomaly detection methods reveal previously unknown schemes, linked entities and hidden crime rings, which can help stem larger losses.
Get a consolidated view of fraud risk.
Identify linkages among seemingly unrelated claims, and identify cross-product fraud. A unique visualization interface lets you see customer claims and policies for all lines of business, and analyze all related activities and relationships at a network dimension. Social network diagrams and sophisticated data mining capabilities give you a better understanding of new fraud threats, enabling you to prevent substantial losses early. And you can stay on top of changing claims fraud trends by continually improving models and adapting the system.
Lower loss-adjustment expenses, and gain a greater competitive advantage.
A sophisticated fraud scoring engine enables you to identify claims fraud with greater speed and accuracy. By quickly determining which claims require further scrutiny and which ones don't, you can significantly reduce false positives – which means a better customer experience. Automatic scoring lets you prioritize higher-value claims, entities and networks, while advanced case handling tools enable more efficient, effective investigations – and a higher ROI per investigator. In addition, all claims settlement amounts are captured within the system for reuse with similar claims in the future.
A single, end-to-end framework uses multiple techniques – automated business rules, predictive modeling, text mining, exception reporting, network link analysis, etc. – to better identify fraudulent activity and stop payments before they are made.
Get to Know SAS Detection and Investigation for Insurance
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