September 13, 2017
Featurespace Cited in Gartner’s Align Your Financial Fraud Detection Strategy With Gartner's Capability Model for Behaviour Analytics and Continuous Risk Assessment
Featurespace, a leader in real-time machine learning fraud prevention using Adaptive Behavioural Analytics, has been cited in Gartner’s July 2017 report on how organisations should “Align Your Financial Fraud Detection Strategy With Gartner's Capability Model” for its Behaviour Analytics and Continuous Risk Assessment capabilities.
According to Gartner’s research on how to Align Your Financial Fraud Detection Strategy With Gartner's Capability Model: “as digital fraud attacks become more sophisticated and identity theft becomes more complex, it's time to rethink fraud's functional detection and protection architecture. Security and risk management leaders must strive for a contextual, risk-based approach to address multiple use cases”.
Featurespace is a leader in Adaptive Behavioural Analytics, delivered via the machine learning ARIC™ platform. ARIC uses anomaly detection to analyse multiple data streams in real time, building individual behavioural profiles for each customer.
ARIC identifies a pattern of normal or ‘good’ behaviour and detects fraud attacks as they happen, reducing the costs associated with managing fraud. At the same time, ARIC reduces the number of genuine transactions incorrectly declined – typically by over 70% – enabling businesses to accept more revenue.
Featurespace’s ARIC platform is deployed live for organisations which have services and products in over 180 countries, including TSYS (the leading US payments processor), Vocalink Zapp, William Hill and Betfair.
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.