Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques

Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution. Early detection is a key factor in mitigating fraud damage, but it involves more specialized techniques than detecting fraud at the more advanced stages. This invaluable guide details both the theory and technical aspects of these techniques, and provides expert insight into streamlining implementation. Coverage includes data gathering, preprocessing, model building, and post-implementation, with comprehensive guidance on various learning techniques and the data types utilized by each. These techniques are effective for fraud detection across industry boundaries, including applications in insurance fraud, credit card fraud, anti-money laundering, healthcare fraud, telecommunications fraud, click fraud, tax evasion, and more, giving you a highly practical framework for fraud prevention.

Book contents:

  1. Fraud: Detection, Prevention, and Analytics!

  2. Data Collection, Sampling, and Preprocessing

  3. Descriptive Analytics for Fraud Detection

  4. Predictive Analytics for Fraud Detection

  5. Social Network Analysis for Fraud Detection

  6. Fraud Analytics: Post-Processing

  7. Fraud Analytics: A Broader Perspective