SAS Secures Technology Patent for Better Fraud Detection Performance
SAS, leader in business analytics software and services, recently received patent approval for “Computer-Implemented Predictive Model Generation Systems and Methods” (US patent 7,788,195 B1) related to technology at the heart of SAS® Fraud Management, an integral component of the SAS Enterprise Financial Crimes Framework for Banking. SAS Fraud Management employs a “Self-Organizing Neural Network Arboretum” (SONNA) modeling capability to build its unique hybrid approach to consortium and custom models.
SAS Fraud Management offers significant improvement in fraud detection performance compared to the performance of regular, non-linear modeling techniques like neural networks. A “score-on-demand” process helps card issuers obtain updated scores based upon the passage of time. The SAS solution provides the creation of risk-based reason factor groups, giving an organization’s fraud operations and analytics groups more insight and context to the risks and reasons behind the model score – optimizing responses and automating actions to a high-scoring transaction.
“With new types of fraud threats on the rise, such as man-in-the-middle and man-in-the-browser, financial institutions are going to need more sophisticated analytics to monitor all transactions and to constantly be looking for abnormalities in behavior,” said George Tubin, Senior Research Director for TowerGroup, a Corporate Executive Board Company. “Vendors that employ enhanced analytical approaches are critical in preventing these types of attacks.”
“Banks will be able to better protect themselves and their customers against fraudsters using these advanced techniques,” said Revathi Subramanian, primary patent inventor and Research and Development Director in the SAS Fraud Modeling Department. “This patent is a demonstration of SAS’ continued commitment to innovation and reinvestment that makes it one of the foremost business analytics companies in the world.”
SAS has developed consortium models for Asia Pacific, Mexico, the United Kingdom and the United States, but the models can also be used in other non-listed regions to drive immediate return on investment.
“SAS feels that customized predictive models are the best way to maximize ROI from a fraud solution,” said Ellen Joyner, Global Marketing Manager, Financial Crimes Prevention at SAS. “We understand that all clients may not have the data history of known fraudsters and their behavior to customize predictive models or the requirement for a customized approach. SAS has developed regional models based upon consortium data that helps SAS to readily deploy ‘out of the box’ analytics across multiple product and channel portfolios.”
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