The rise of financial crime threatens the security of economic systems around the world. And even if better controls and government regulations have improved security for financial systems, they still do not prevent crimes from occurring altogether.

And with financial crime risk higher than ever, institutions need to move beyond a traditional reactive approach to fraud to a more proactive one. This means that fraud management systems must be able to identify true fraud from false positives and customer impact, which can be as or more damaging and costly than actual fraud.

The solution to stop scammers in a proactive manner is to use adaptive behavioral analytics and machine learning. Knowing when a customer’s spending behavior is out of character provides a better path forward. Rather than using blanket fraud-detection criteria, adaptive behavioral analytics creates customer profiles based on payment activity and frequency. These profiles are then used to flag fraudulent activity before it occurs.

The new partnership from Featurespace and FIS® aims to do just that. It aims to help financial institutions, acquirers, issuers and payment processors stop scammers and fraudsters by utilizing adaptive real-time individual behavioral analytics and machine learning that adapts to changing behavior. Using real-time transaction monitoring, Featurespace’s ARIC™ Risk Hub blocks on average 75% of fraud attacks as they occur with a significant reduction in false positive rate against incumbent systems.

Read full article >> Stay ahead of fraud with financial crime risk management