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SAS Releases Fraud Framework

The newly released SAS Fraud Framework solution includes insurance industry specific components to detect and prevent fraudulent claims activity.

SAS, a Cary, N.C.-based business analytics software and services provider, has unveiled the SAS Fraud Framework, which is designed to help detect and prevent both line-of-business and cross-channel enterprise fraud by increasing fraud detection rates, reducing false positives and streamlining investigative resources. The new framework includes components that support alert and case management as well as detection and alert generation capabilities.

The framework leverages business rules, anomaly detection, predictive models and social network analysis technologies to prevent, detect and investigate fraud. At the core of the framework, the company says, is a profiling engine that scores individuals, accounts, products and networks based on rules, fraud scores and links to known fraudsters. An enterprise view of fraud exposure and risk is provided by the consolidation of alerts from multiple systems, according to a press release.

Insurance-specific functionality included in the framework is aimed at detecting and preventing fraudulent claims. The anti-fraud engine, the company says, uses a combination of techniques to assign each claim a fraud score at each stage of the claims process. Alerts are created for suspicious claims, which are then routed to special investigation units (SIUs).

SAS Social Network Analysis is a featured component of the new framework. A new solution, Social Network Analysis provides investigators with an interface that enables access to full customer details and all related parties and networks, allowing for the analysis of related activities and relationships within a network such as shared addresses, telephone numbers, employment, account ownership and other key transactional data points.

SAS suggests that the social network solution's network visualization interface will help investigators see network connections more clearly and enable them to uncover previously unknown relationships. "With SAS Social Network Analysis, it is possible to find previously unknown relationships that by themselves seem innocuous, but in concert are clearly fraudulent," said Dr. John Brocklebank, Vice President of SAS Solutions OnDemand, in a press release.

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