Yes, It’s Possible—Frictionless Account Fraud Protection

Over the past few years, bank account fraud has become one of the largest threats against financial institutions (FIs). Just last year, there’s been over $52B in identity fraud losses affecting 42 million U.S. consumers. And this grew 79% y-o-y. Community banks and credit unions must find a way to balance methods of managing fraudulent activity with attracting new customers. Otherwise, they may be left behind. And the stakes are higher than ever. At the same time FIs are looking at high application abandonment rates.

Manage Fraud & Compliance Risk Management in a Single Solution

Many community-based financial institutions’ risk management tools now consist of a disjointed collection of point solutions and siloed risk management functions. But, as the lines begin to blur between different types of risk, continuing a disjointed approach to fraud and compliance risk management will inevitably result in missed vulnerabilities to be exploited by malicious actors.

Machine Learning to Reduce End-User Friction

Digital change happens at the speed of light, and fraudsters move nearly as quickly to exploit vulnerabilities and gaps in fraud prevention capabilities. Financial institutions cannot afford to leave protection up to chance.

Machine Learning in Fraud Prevention

About Fraud situation, Fraud is more sophisticated with ML, Why machine learning, Current applications, Drawbacks, Future applications, Conclusion