Detecting credit card fraud with Red Hat Decision Manager 7

Detecting credit card fraud with Red Hat Decision Manager 7

Red Hat Decision Manager provides a vast array of decision management functionality. From the Decision Tables feature in the new Decision Model and Notation (DMN) v1.1, which implements the full FEEL Compliance Level 3 of the DMN specification, to Predictive Model Markup Language (PMML).

Another powerful feature is the Complex Event Processing (CEP) engine. This engine provides the ability to detect, correlate, abstract, aggregate or compose and react to events. In other words, the technology provides techniques to infer complex events from simple events, react to the events of interest, and take actions. The main difference between CEP and normal rules execution is the notion of time. Where standard rules execution in Decision Manager deals with facts and reasoning over these facts, the CEP engine focusses on events. An event represents a significant change of state at a particular point in time or interval.

Recently, I was asked to demonstrate how Decision Manager CEP can be used in a real-time credit card fraud detection system. One of the requirements I was presented with ended up in an interesting rule implementation that forms the basis of this article. The requirement was defined as follows:

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