Statistical Techniques for Forensic Accounting

SAURAV DUTTA (Albany, NY) is Associate Professor and former chair of the Department of Accounting, Business Law and Taxation at Univ. of Albany. In 2011, he served as Academic Fellow in the SEC's Office of Chief Accountant. Dutta's research interests are in applying statistical and analytical methodologies to accounting and auditing. He has published 20 research papers, and conducted seminars at universities including Harvard, Oxford, NYU, and Maastricht. Invited by AICPA to present on statistics for forensic accounting and litigation, he has been engaged as an expert to design statistical procedures to verify claims against Worldcom, Global Crossing, Cendant, GM, and HealthSouth.

Foreword   xiii
Acknowledgments   xv
Preface   xviii
1 Introduction: The Challenges in Forensic Accounting   1
1.1 Introduction   1
1.2 Characteristics and Types of Fraud   3
1.3 Management Fraud Schemes   7
1.4 Employee Fraud Schemes   11
1.5 Cyber-crime   17
1.6 Chapter Summary   18
1.7 Endnotes   19
2 Legislation, Regulation, and Guidance Impacting Forensic Accounting   21
2.1 Introduction   21
2.2 U.S. Legislative Response to Fraudulent Financial Reporting   22
2.3 The Emphasis on Prosecution of Fraud at the Department of Justice   24
2.4 The Role of the FBI in Detecting Corporate Fraud   26
2.5 Professional Guidance in SAS 99   27
2.6 Chapter Summary   28
2.7 Endnotes   29
3 Preventive Measures: Corporate Governance and Internal Controls   31
3.1 Introduction   31
3.2 Corporate Governance Issues in Developed Economies   33
3.3 Emerging Economies and Their Unique Corporate Governance Issues   34
3.4 Organizational Controls   39
3.5 A System of Internal Controls   41
3.6 The COSO Framework on Internal Controls   46
3.7 Benefits, Costs, and Limitations of Internal Controls   52
3.8 Incorporation of Fraud Risk in the Design of Internal Controls   56
3.9 Legislation on Internal Controls   58
3.10 Chapter Summary   58
3.11 Endnotes   60
4 Detection of Fraud: Shared Responsibility   61
4.1 Introduction   61
4.2 Expectations Gap in the Accounting Profession   64
4.3 Responsibility of the External Auditor   66
4.4 Responsibility of the Board of Directors   68
4.5 Role of the Audit Committee   71
4.6 Managements Role and Responsibilities in the Financial Reporting Process   75
4.7 The Role of the Internal Auditor   78
4.8 Who Blows the Whistle   80
4.9 Chapter Summary   84
4.10 Endnotes   85
5 Data Mining   89
5.1 Introduction   89
5.2 Data Classification   91
5.3 Association Analysis   93
5.4 Cluster Analysis   95
5.5 Outlier Analysis   98
5.6 Data Mining to Detect Money Laundering   100
5.7 Chapter Summary   103
5.8 Endnotes   103
6 Transitioning to Evidence   105
6.1 Introduction   105
6.2 Probability Concepts and Terminology   106
6.3 Schematic Representation of Evidence   108
6.4 Information and Evidence   110
6.5 Mathematical Definitions of Prior, Conditional, and Posterior Probability   110
6.6 The Probative Value of Evidence   114
6.7 Bayes Rule   117
6.8 Chapter Summary   122
6.9 Endnote   123
7 Discrete Probability Distributions   125
7.1 In...