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

Book Title

 By Bart Baesens, Veronique Van Vlasselaer and Wouter Verbeke 


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:
Copyright 2015
Hardcover, 400 Pages
Wiley; 1 edition

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