Modern FRM

The modern payments value chain is long and complex, with data flowing back and forth continuously. This data is living and ever-changing but locked in silos. Conventional Fraud Analytics architecture systems are built on systems of record and designed to analyze large volumes of historical data to produce fraud insights and predictions.

Conventional fraud analytics systems are siloed and not designed to keep up with the wide array of attacks on data and data sources. To keep up with this rapidly growing threat, payment providers must evolve from the traditional, siloed method of fraud detection to a proactive, analytic approach; the models to be used are trained on historical data, frozen, then weighted or adjusted in batches. This led to almost no co-operative learning and decision making.