NatWest and Featurespace Partner for Real-Time, Enterprise-Wide Fraud Prevention and Transaction Monitoring
NatWest has agreed a strategic partnership with Featurespace to profile and monitor payments and account activity to prevent fraud and scams using Featurespace’s ARIC™ Risk Hub. The platform has the ability to detect and reduce third-party fraud losses and prevent overall fraud before the point of payment.
"The fraud challenge requires an innovative partnership to stay ahead of threats posed to our dynamic payment landscape and we are delighted to be working together to solve this problem," said Martina King, CEO of Featurespace.
With Featurespace's ARIC platform, NatWest enhances its ability to detect and reduce third-party fraud losses and prevent overall fraud before the point of payment.
"The only way to consistently stop multifaceted fraud and protect our customers is to learn about customers' specific behaviors, recognize what's normal and immediately detect anomalies," said Alasdair MacFarlane, Head of Fraud Prevention & Response at NatWest. "Featurespace allows us to more accurately assess risk and authenticate activity across multiple channels, while facilitating a much stronger incident management process."
The ARIC platform, powered by machine learning and Featurespace's Adaptive Behavioral Analytics, detects anomalies and risk scores each event to predict the likelihood of fraud. In addition, the ARIC platform reduces the number of false alerts, allowing fraud analysts to dedicate their time to reviewing genuine fraud alerts and removing friction in the payments process for customers.
About Featurespace - www.featurespace.com
Headquartered in the U.S. and U.K. and with offices in Atlanta, Cambridge and London, Featurespace™ is the world-leader in risk prevention and creator of the ARIC™ Risk Hub, a real-time AI machine learning software that risk scores events in more than 180 countries to prevent fraud and financial crime.
The ARIC platform combines unique Adaptive Behavioral Analytics and anomaly detection to automatically identify risk and catch new fraud attacks and suspicious activity in real-time. The increased accuracy of understanding 'good' behavior strikes the balance between improving the detection of suspicious activity, while also reducing the number of false alerts, to improve operational efficiencies.