Working directly with the financial services industry, Featurespace has developed a PSD2-ready fraud solution that can be quickly deployed by banks to protect their customers and be in immediate compliance with new and pending regulations.
An industry first, Featurespace's real-time machine learning ARIC platform is now equipped with predefined PSD2-specific data feeds and configurations – including rules and adaptive behavioral analytics – and can be enterprise-ready within three months. Many financial institutions have already successfully deployed the PSD2-ready ARIC platform, with one large organization completing a two-day implementation through cloud delivery.
Martina King, CEO of Featurespace, said, “We have worked tirelessly with banks to build a tailor-made, compliant solution for the industry, which financial institutions can deploy quickly and be ready to protect their customers without increasing friction."
The ARIC platform understands individual behaviors in real-time to detect consumer anomalies and automatically decide which transactions to escalate to Strong Customer Authentication. Using industry proven Adaptive Behavioral Analytics invented by Featurespace, ARIC enables banks to optimize for the highest fraud prevention rates, while simultaneously reducing false positives.
About Featurespace – www.featurespace.com
Headquartered in the U.K. and U.S. 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 behavioural analytics and anomaly detection to automatically identify risk and catch new attacks as they happen. The increased accuracy of understanding behaviour 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 due to traditional rules by as much as 70 percent.
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