SPSS Offering Solution for Fighting Fraud

May 24, 2005

Chicago-based SPSS, a provider of predictive analytics software, has unveiled a new solution that will reportedly reduce insurance fraud, significantly improve the claims process and cut costs.

SPSS’ PredictiveClaims, an application based on real-time predictive analytic technology, integrates with existing claims-management systems to instantly determine which claims qualify for immediate approval and which are potentially fraudulent. “Fast-track claims handling” reportedly improves the efficiency of claim handling and customer service.

PredictiveClaims automatically analyzes all claims entering the system – from any channel – against risk profiles and external fraud databases. PredictiveClaims will either approve a claim for processing or flag it for investigation. The application can also generate “smart” questions that prompt a claim handler to ask customers for critical new information that can confirm the likelihood of fraud.

PredictiveClaims enables property and casualty insurers to:

— Approve legitimate insurance claims quickly to satisfy valuable customers and minimize loss adjustment expenses and claim handling costs;

— Identify potential fraud at an early stage with a high degree of accuracy – even with large claim volumes;

— Understand why certain claims are flagged as suspicious, so insurance Special Investigation Units (SIUs) know where to focus their investigations;

— Combine and analyze data from multiple internal and external sources, including federal and insurance industry databases;

— Integrate with existing claims management systems without extensive customization or lengthy implementation periods;

— Analyze textual claim data, such as accident descriptions, for other indicators of fraudulent behavior.

For more information about PredictiveClaims and other SPSS predictive analytic applications, visit www.spss.com.

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