Using Analytics to Detect Possible Fraud: Tools and Techniques

By: Pamela S. Mantone, CFE, CPA

This book’s author is a CFE

Book cover for using data analytics to detect fraud
Using Analytics to Detect Possible Fraud


"Using Analytics to Detect Possible Fraud: Tools and Techniques" is a practical overview of the first stage of fraud examination, providing a common source of analytical techniques used for both efficiency and effectiveness in fraud examinations. The book is written clearly so that those who do not have advanced mathematical skills will be able to understand the analytical tests and use the tests in a forensic accounting setting. It also includes case studies and visual techniques providing practical application of the analytical tests discussed.

This book explores:

  • Using various financial ratios and other analytical tests to identify potential anomalies in financial statement data
  • Applying the Beneish M-Score Model, Pitoroski F-Score Model, Lev-Thiagarajan’s 12 Signals, and Benford’s Law to find potential financial statement manipulation
  • Identifying unusual variations and inconsistencies in financial statements by using three different perspectives in analyzing accruals

Product Details

This book's author is a CFE.
Label Value
ISBN 978-1-118-58562-7
Publisher John Wiley & Sons Publishing
Published 2013
Pages 340
Format Hardcover

Table of Contents

Chapter 1 Overview of the Companies
Chapter 2 The “Norm” and the “Forensic” Preliminary Analytics: Basics Everyone Should Know
Chapter 3 The Importance of Cash Flows and Cash Flow Statements
Chapter 4 The Beneish M-Score Model
Chapter 5 The Accruals
Chapter 6 Analysis Techniques Using Historical Financial Statements and Other Company Information
Chapter 7 Benford's Law, and Yes—Even Statistics
Chapter 8 Grading the Four Companies

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