Fraud and Fraud Detection: A Data Analytics Approach, + Website

Preface

FRAUD AND FRAUD DETECTION takes a data analytics approach to detecting anomalies in data that are indicators of fraud. The book starts by introducing the reader to the basics of fraud and fraud detection followed by practical steps for obtaining and organizing data in usable formats for analysis. Written by an auditor for auditors, accountants, and investigators, Fraud and Fraud Detection enables the reader to understand and apply statistics and statistical-sampling techniques. The major types of occupational fraud are reviewed and specific data analytical detection tests for each type are discussed along with step-by-step examples. A case study shows how zapper or electronic suppression of sales fraud in point-of-sales systems can be detected and quantified.

Any data analytic software may be used with the concepts of this book. However, this book uses CaseWare IDEA software to detail its step-by-step analytical procedures. The companion website provides access to a fully functional demonstration version of the latest IDEA software. The site also includes useful IDEAScripts that automate many of the data analytic tests.

Fraud and Fraud Detection provides insights that enhance the reader’s data analytic skills. Readers will learn to:

• Understand the different areas of fraud and their specific detection methods.
• Evaluate point-of-sales system data files for zapper fraud.
• Understand data requirements, file format types, and apply data verification procedures.
• Understand ...