Summary
Artificial intelligence went through a long period of maturation plagued by high rates of false positives and inexplicable decisioning. But AI and machine learning (ML) tools have since become part of leading fraud management solutions. AI also plays an important role in situations where training data for developing risk models is unavailable. Reducing false positives in fraud management use cases is essential to maintaining confidentiality, integrity, and empathy when risk-scoring customer transactions. This report identifies key fraud management use cases where AI can help and maps how security and risk (S&R) professionals can use major AI technologies in each situation.
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