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Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques

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THE DEFINITIVE GUIDE TO THE DETECTION AND PREVENTION OF FRAUD THROUGH DATA ANALYTICS Catch fraud early! Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques shows you how with a thorough overview of how to prevent losses and recover quickly as well as the security issues you need to address now. Exploring how auditors, corporate security prevention managers, and fraud prevention professionals can stay one step ahead of cyber criminals, this book addresses the different types of analytics in detecting fraud, including descriptive analytics, predictive analytics, and social network analysis. Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques offers a current, state-of-the-art detection and prevention methodology, describing the data necessary to detect fraud. Taking you from the basics of fraud detection data analytics, through advanced pattern recognition methodology, to cutting-edge social network analysis and fraud ring detection, this book presents essential coverage of: * The fraud analytics process model * Big data * Break point/peer group analysis * Anomaly detection * Linear/logistic regression * Neural networks * Ensemble methods * Social network metrics * Bipartite graphs * Community mining * Visual analytics * Model monitoring and backtesting Insightful and clearly written, this hands-on guide reveals what you need to know about fraud analytics and the secret to putting historical data to work in the fight against fraud.
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