ARIC White Label delivers the full functionality of the award-winning ARIC Fraud and Risk platform - including adaptive behavioral analytics and biometrics - allowing processors and acquirers to offer their customers the industry's most advanced fraud and risk prevention tools. Fully brandable, ARIC White Label easily integrates into clients' systems to provide:
- Multi-tenancy: Fraud detection strategies can be configured and simultaneously deployed, including rules and adaptive models at the individual merchant- and issuer-level, over specific groups and across entire portfolios;
- Instant Onboarding: Clients can set templates for the levels of access provided to tenants;
- Full Data Segregation: Tenants cannot access data of other tenants;
- Complete control over rules
- Model deployment – Featurespace’s or customer’s own
- Reporting and Incident Management.
With ARIC White Label, clients can also incorporate and combine Featurespace's Adaptive Behavioral Analytics with their existing models to build profiles of normal behavior for every consumer and then deliver custom risk scores of each interaction at every touchpoint, ensuring the highest accuracy when determining if an event is genuine or fraudulent.
"ARIC White Label is deployed and powerfully delivering for our customers," said Dave Excell, founder and CTO at Featurespace. “Our technology will help to provide best-in-class fraud and risk protection for customers who might otherwise have not been able to benefit from the ARIC Fraud and Risk Hub.”
To see a live demo of ARIC White Label, visit Featurespace's booth (#2109) at Money 20/20 in Las Vegas or to schedule a demo or a meeting with Featurespace during or after the event, please contact [email protected].
About Featurespace
Headquartered in the UK and US, 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 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 due to traditional rules by as much as 70 percent.