Fraud Analytics: Using Descriptive, Predictive, and Social Network Techniques

By Bart Baesens, Veronique Van Vlasselaer and Wouter Verbeke

Book cover for fraud analytics
Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques


The sooner you detect fraud, the more likely you are to reduce losses, increase recovery and tighten security. Detecting fraud at an early stage, though, is more difficult than detecting it later and requires specific techniques.

"Fraud Analytics" provides you with a comprehensive overview of fraud detection analytical techniques and provides implementation guidance for an effective fraud prevention solution to help you detect fraud early.

You will learn how to:

  • Detect fraud sooner
  • Examine fraud patterns in historical data
  • Use labeled, unlabeled and networked data

Topics covered include:

  • The fraud analytics process model
  • Big data
  • Anomaly detection
  • Neural networks
  • Social network metrics
  • Community mining
  • Visual analytics

Product Details

Label Value
ISBN 978-1-119-13312-4
Publisher John Wiley & Sons
Published Copyright 2015
Pages 400
Format Hardcover

Table of Contents

List of Figures
Chapter 1 Fraud: Detection, Prevention and Analytics!
Chapter 2 Data Collection, Sampling and Preprocessing
Chapter 3 Descriptive Analytics for Fraud Detection
Chapter 4 Predictive Analytics for Fraud Detection
Chapter 5 Social Network Analysis for Fraud Detection
Chapter 6 Fraud Analytics: Post-Processing
Chapter 7 Fraud Analytics: A Broader Perspective

Ordering and Returns

Satisfaction Guarantee

If you are not 100% satisfied with any ACFE product, you may return it to us, provided it is in excellent condition, for a full refund of the item minus the cost of shipping. Toolkits and bundles may only be returned as a complete set.

Ordering & Returns Policy