Benford's Law: Applications for Forensic Accounting, Auditing, and Fraud Detection(Wiley Corporate F&A)

A powerful new tool for all forensic accountants, or anyone who analyzes data that may have been altered Benford's Law gives the expected patterns of the digits in the numbers in tabulated data such as town and city populations or Madoff's fictitious portfolio returns. Those digits, in unaltered data, will not occur in equal proportions; there is a large bias towards the lower digits, so much so that nearly one-half of all numbers are expected to start with the digits 1 or 2. These patterns were originally discovered by physicist Frank Benford in the early 1930s, and have since been found to apply to all tabulated data. Mark J. Nigrini has been a pioneer in applying Benford's Law to auditing and forensic accounting, even before his groundbreaking 1999 Journal of Accountancy article introducing this useful tool to the accounting world. In Benford's Law, Nigrini shows the widespread applicability of Benford's Law and its practical uses to detect fraud, errors, and other anomalies. Explores primary, associated, and advanced tests, all described with data sets that include corporate payments data and election data Includes ten fraud detection studies, including vendor fraud, payroll fraud, due diligence when purchasing a business, and tax evasion Covers financial statement fraud, with data from Enron, AIG, and companies that were the target of hedge fund short sales Looks at how to detect Ponzi schemes, including data on Madoff, Waxenberg, and more Examines many other applications, from the Clinton tax returns and the charitable gifts of Lehman Brothers to tax evasion and number invention Benford's Law has 250 figures and uses 50 interesting authentic and fraudulent real-world data sets to explain both theory and practice, and concludes with an agenda and directions for future research. The companion website adds additional information and resources.

Table of Contents:
Foreword xi Preface xiii About the Author xix Chapter 1: Introduction and Mathematical Foundations 1 Benford’s Expected Digit Frequencies 5 Defining the First and First-Two Digits 6 Digit Patterns of U.S. Census Data 8 Logging on to Benford’s Law 10 General Significant Digit Law 13 Log and Behold, the Census Data 13 Love at First Sight 15 Mantissa Test and Census Data 19 Number of Records and Benford’s Law Tests 20 When Should Data Conform to Benford’s Law? 21 Conclusions 23 Chapter 2: Theorems, Truisms, and a Little Trivia 25 Digits of Corporate Payments Data 26 Digits of Lake Data 28 Scale Invariance Theorem 31 Mean Absolute Deviation 34 Scale Invariance and Census Data 34 Scale Invariance and Corporate Payments 35 Scale Invariance and Lake Data 36 A Level Playing Field Becomes Benford 38 Multiplication by 1/X 42 All Distributions Lead to Benford 43 Getting a Gripf on Benford and Zipf 46 Conclusions 50 Chapter 3: More Formulas and Facts, and a Little Fibonacci 51 Fibonacci Numbers 51 Lucas Numbers 53 Back to Square One 55 3n+1 Problem 58 Ultimate Uniform Distribution 60 Benford Embraces Other Bases 62 Nigrini’s Second Last Theorem 65 Conclusions 69 Chapter 4: Primary Benford’s Law Tests 71 Corporate Payments Data 72 Data Profile 72 First Come, First Served 74 Playing Second Fiddle 75 First-Two Digits Test 78 Running the Digit Tests in Excel 80 Running the Digit Tests in Access 83 Conclusions 87 Chapter 5: Advanced Benford’s Law Tests 89 Summation Test 90 Running the Summation Test in Excel 94 Running the Summation Test in Access 95 Second-Order Test 97 An Analysis of Payments Data 102 An Analysis of Journal Entry Data 104 An Analysis of Census Data 107 Running the Second-Order Test in Excel 108 Excel, Thanks a Million(s) 110 Scale Invariance and the Second-Order Test 113 Conclusions 114 Chapter 6: Associated Benford’s Law Tests 117 Number Duplication Test 117 An Analysis of Payments Data 119 An Analysis of Census Data 121 Running the Number Duplication Test in Excel 122 Running the Number Duplication Test in Access 126 Last-Two Digits Test 129 An Analysis of Payments Data 130 An Analysis of Census Data 131 An Analysis of Election Results 132 Running the Last-Two Digits Test in Excel 135 Running the Last-Two Digits Test in Access 136 Distortion Factor Model 138 Distortion and the Census Data 145 Conclusions 146 Chapter 7: Assessing Conformity to Benford’s Law 149 Z-Statistic 150 Chi-Square Test 153 Kolmogorov-Smirnoff Test 157 Mean Absolute Deviation Test 158 The Logarithmic Basis of Benford’s Law 160 Creating a Perfect Synthetic Benford Set 163 Mantissa Arc Test 165 Conclusions 169 Chapter 8: Examples of Fraudulent Data 171 The Inside Story 172 The Vendor Who Never Was 174 Not Paying Attention 175 Funny Money 177 The Heart of the Matter 181 Going the Extra Mile 182 Laugh All the Way to the Bank 184 Culture Shock 187 Having a Bad Hair Day 189 An Unclean Bill of Health 191 Turning the Table on Tax Evasion 193 Conclusions 196 Chapter 9: Fraudulent Financial Statements, Part I 199 Number Crunching 200 Wrong Numbers 205 A Look at Enron’s and AIG’s Numbers 207 Figuring Out the Controllers 210 Conclusions 213 Chapter 10: Fraudulent Financial Statements, Part II 215 Digital Yoga by Absaroka 216 Can’t See the Forest for the Trees 218 Digit a Little Deeper into Papua New Guinea 221 The Good, the Bad, and the Ugly 227 Dig a Little Deeper 233 There Are More Questions than Answers 237 Conclusions 244 Chapter 11: Madoff and Other Ponzi Schemes 247 The Madoff Claims 248 Don’t Bank on Kaupthing 249 The Whole Ball of Waxenberg 252 General Motors Demoted to Private 253 Chrysler Unable to Dodge Bankruptcy 255 Discussion of the Claims Results 258 A Review of the Madoff Returns 259 Apple, Dell, Berkshire, and Benford 262 Discussion of the Returns Results 265 Chapter 12: Earth Science and Income Tax Applications 267 Still Waters Run Deep 268 The Lay of the Lake 274 For a Few Dollars Less 281 A Clean Bill of Clinton 286 Conclusions 290 Chapter 13: Future Directions and Conclusions 293 My Law 295 Insights into Number Invention 300 Lehman’s Charitable Gifts 306 The Bottom Line 310 Glossary of Selected Terms 315 References 323 Index 327

About the Author :
MARK J. NIGRINI, PHD, is a professor at The College of New Jersey where he teaches forensic accounting courses. His research involves advanced theoretical work on Benford's Law and the legal process surrounding fraud convictions. Nigrini is also the author of Forensic Analytics (Wiley), which describes tests to detect fraud, errors, estimates, and biases in financial data. He has been published in national media including the Wall Street Journal and has published papers on Benford's Law and accounting in academic and professional journals. Nigrini regularly presents professional seminars for accountants and auditors in North America, Europe, and Asia with recent events in Singapore, Switzerland, and New Zealand.