Apama: Fraud Detection and Heat Maps

A few days ago in Visualization Reloaded I touched upon the subject of heat maps.  In that post the application context was monitoring a massively parallel online gaming platform using a combination of event processing technologies by StreamBase and SL

Today, I was reminded of another heat map created by Progress Apama during a leisurely morning viewing of a Fox Business New video interview with John Bates.  This time the context is the detection of patterns of insider trading.  

Apama Heat Map

In this graphic above (click the image for a larger view) Apama uses a heat map to visualize suspicious trading activity in real time.   Also, you might be interested to know that the cool heat map in this use case is based on the event processing visualization platform by SL Corporation, similar to the heat map in this use case by StreamBase, Simultronics and SL.

Amazingly, in the Fox Business interview John mentions an interesting statistic.   During certain business situations, like mergers and acquisitions, experts have estimated that up to 30 percent of trading activity can be linked to insider trading.   The event processing goal, of course, is to detect fraud sooner than later, minimizing fraudulent market transactions and their influence on the market.

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