The ability to detect fraudulent card payments is becoming increasingly important as the world moves towards a cashless society. For decades, banks have relied on building complex mathematical models to predict whether a given card payment transaction is likely to be fraudulent or not. These models must be both accurate and precise—they must catch fraudulent activity when it occurs, but must not incorrectly predict fraud for valid transactions. Such false positives can cause embarrassing customer experiences.
These mathematical models for detecting fraud are developed using machine learning (ML) algorithms. Data scientists provide large samples of both valid and fraudulent …
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