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Harnessing the Power of ML: Essential Use Cases for Fraud and Risk Leaders

Financial fraud is growing and it’s expensive.

A mix of factors are combining to create a lower entry barrier for fraudsters and high-risk customers. This makes it imperative for financial services institutions (FSIs) to prevent fraudulent activity from occurring in the first place.
Implementing ML/AI tools to predict risk levels and the likelihood of fraud enables fraud and risk leaders to fight losses by successfully pre-screening applicants to avoid engagement with high-risk customers and/or fraudsters.
Here are three ways you can use ML to detect fraud and high-risk transactions early, before you move forward with ineligible applicants or fraudsters.