Fraud detection and machine learning: What you need to know

All things change, and you must adapt over time. Ongoing monitoring of machine learning fraud detection systems is imperative for success. As populations and the underlying data shift, expected system inputs degrade and therefore have an impact on overall performance. This isn't unique to machine learning systems; rule-based systems have the same challenge. But newer machine learning methods can adapt to new and unidentified patterns as underlying changes occur. This eliminates some, but not all, of the machine learning retraining and evaluation steps.