Overcoming Cross-Channel Challenges with Next-Gen Fraud Prevention
Today’s credit union members enjoy the freedom of accessing their accounts through a wide variety of connected devices, including mobile phones, computers, tablets and smart watches. Yet, with all the conveniences they bring, these devices also provide many points of access to members’ financial data, putting them and their credit unions at risk of falling victim to cross-channel fraud. For a long time, fraud solutions have leveraged machine learning and pre-programmed rules to catch criminals in the act. However, today's interconnectivity has allowed fraudsters to innovate their tactics and static rules do not prevent against new attacks.
More than a decade ago, adaptive behavioral analytics was invented in the U.K., creating the next generation of fraud prevention. By understanding individual behaviors, these analytics learn what activities are genuine and what looks suspicious.
Featurespace named Best in Class in Aite Machine Learning Vendor Evaluation
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Headquartered in the U.S. and U.K. and with offices in Atlanta, Cambridge and London, Featurespace™ is the world-leader in fraud prevention and creator of the ARIC™ platform, a real-time AI machine learning software that risk scores events in more than 180 countries.
The ARIC platform combines adaptive behavioral analytics and anomaly detection to automatically identify risk and catch new attacks as they happen. The increased accuracy of understanding behavior strikes the balance between improving fraud and risk detection and operational efficiencies, while also reducing the number of genuine transactions that would be incorrectly declined by as much as 70 percent.