Forensic Analytics: Methods and Techniques for Forensic Accounting Investigations, 2nd Edition
The revised and updated Second Edition of "Forensic Analytics" offers an essential guide to detecting accounting fraud, biases and errors in financial data. You will explore the methods and techniques you can use to identify anomalies in both corporate and public sector data including errors, biases, duplicates, number rounding and omissions.
"Forensic Analytics" is written as a resource for professional accountants and auditors who typically lack a rigorous understanding of complex math and statistics. While the book is filled with fascinating vignettes and illustrations, it puts the focus on the quantitative and computing aspects of forensics. One lengthy chapter discusses how to detect financial statement misconduct through the use of various statistical approaches. The use of Benford's Law, descriptive statistics, correlation and timeseries analysis are also reviewed. The book's data interrogation methods are based on common statistical techniques and the author's own research in the field. The author shows how to use Access and Excel in a forensic framework to help connect the dots and to reveal any red flags.
This revised Second Edition contains updates to Access and Excel that help detect anomalies and potential fraud, a review of the use of R, a flexible and free program that can do almost anything when it comes to data analysis, and many fresh fraud cases that complement the techniques presented. "Forensic Analytics" provides the information and examples needed to help you hone your skills to become a forensics-related analytics expert in your organization.
Table of Contents
|Chapter 1||Using Microsoft Excel for Forensic Analytics|
|Chapter 2||The Initial High-Level Overview Tests|
|Chapter 3||Benford’s Law: The Basic Tests|
|Chapter 4||Benford’s Law: Advanced Topics|
|Chapter 5||Benford’s Law: Completing The Cycle|
|Chapter 6||Identifying Anomalous Outliers: Part 1|
|Chapter 7||Identifying Anomalous Outliers: Part 2|
|Chapter 8||Identifying Abnormal Duplications|
|Chapter 9||Comparing Current Period and Prior Period Data: Part 1|
|Chapter 10||Comparing Current Period and Prior Period Data: Part 2|
|Chapter 11||Identifying Anomalies In Time-Series Data|
|Chapter 12||Scoring Forensic Units for Fraud Risk|
|Chapter 13||Case Study: An Employee’s Fraudulent Tax Refunds|
|Chapter 14||Case Study: A Supplier’s Fraudulent Shipping Claims|
|Chapter 15||Detecting Financial Statement Fraud|
|Chapter 16||Using Microsoft Access and R For Analytics|
|Chapter 17||Concluding Notes on Fraud Prevention and Detection|
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