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This article Event-Based Analytics: Getting it Right came by my desk today. The key example used is for credit card fraud detection. Now Fraud detection is something I blog about fairly often (see here for example), and is something of a specialty of my employer (Fair Isaac) and much of the article resonated with me. All of Ajay's examples, however, are about event-based decisioning that uses both analytics and rules. The analytics may do the heavy lifting in the scenarios he outlines, but the application of the conclusion of the analytic must be executed by business rules suitable to the situation. For instance, each credit card issuer will have different rules about how to apply the result of the (neural network) analytic model that predicts the likelihood of fraud for a given transaction. A marketer might use rules about the context to decide how to use an analytic that predicts risk of churn and so on. Rules and analytics make for effective decisioning and event-based decisioning is on the rise. It's just not only about analytics.

Posted by jtaylor in Business Rules • Decision Technologies • Predictive Analytics |Digg This|Add to del.icio.us

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