SPSS Says Its New Technology Can Predict Fraudulent Claims

Chicago-based SPSS recently unveiled a new software product it said will 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.

PredictiveClaims automatically analyzes all claims entering the system — from any channel — against risk profiles and external fraud databases, the firm said in a statement. PredictiveClaims is designed to either approve a claim for processing or flag it for investigation. The application reportedly 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 is designed to enable property/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.

Eight of the top 10 global property/casualty insurers on the 2004 FORTUNE Global 500 list are SPSS customers, the company said.

Topics Fraud Claims Tech