White Paper

Risk analytics for fraud prevention: Top use cases in banking

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The rapidly changing threat landscape is making it easier for malicious actors to commit financial fraud. Worse, organized crime rings are taking advantage of COVID-19 to drive up fraud losses for financial institutions. In order to combat the onslaught of attacks, fraud detection and prevention systems need the ability to do real-time fraud analysis through analytics.

To create a better understanding of the value of a risk analytics system driven by machine learning, this white paper explains continuous fraud monitoring and dynamic risk assessment in the context of the top use cases in banking.