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Differentiating Data Analytics from Data Analysis

In an interview with ZDNet, Josh Sullivan, leader of the data science and analytics practice at Booz Allen Hamilton, discusses the importance of human analysis complementing machine analytics. While the focus is on big data for any application, the discussion and points made provide insights and important considerations very relevant to modeling and analytics for fraud and risk management.

While card issuers and financial institutions have long employed modeling and analytics as a fraud prevention technique it is now becoming more common among eCommerce merchants. As a result we are seeing much more talk about machine learning, neural networks and advanced statistical models in the risk management marketplace. Although custom analytic modeling risk services require sophisticated platforms and technology, the reality is that a human element is required to ensure these services continue to run effectively.

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