Together, Reducing Fraud Worldwide

Using Analytics to Detect Possible Fraud: Tools and Techniques


  Ratings and Reviews

 using-data-analytics-to-detect-fraud
 

 By Pamela S. Mantone, CFE, CPA 

 

 

Description: 

 

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:
Copyright 2013
ISBN 978-1-118-58562-7
Hardcover, 340 pages
John Wiley & Sons Publishing
 

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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