Forensic Analytics: Methods and Techniques for Forensic Accounting Investigations

ISBN-13: 9781119585763 / Angielski / Twarda / 2020 / 544 str.

Mark J. Nigrini

Spis treści

List of Cases xiiiAbout the Author xvPreface xviiAbbreviations xxiAnalytics Software Used xxvIntroduction 1Temptation in an Occupation 2Fraudulent Checks Written by the CFO 4Fraudulent Purchases Made by a Purchasing Manager 7Donna was a Gamblin' Wreck at Georgia Tech 9Forensic Analytics 11An Overview of Tableau 13The Risk Assessment Standards 19Discussion 21Chapter 1: Using Microsoft Excel for Forensic Analytics 23The Fraud Types Relevant to Forensic Analytics 23The Main Steps in a Forensic Analytics Application 25The Final Report 27An Overview of Excel 28Importing Data into Excel 29Some Useful Excel Formatting Features 30Protecting Excel Spreadsheets 32The Valuable "IF" Function 33The PIVOTTABLE Routine 36The Valuable VLOOKUP Function 38Using Excel Results in Word Files 40Excel Warnings and Indicators 42Excel Dashboards 43Dashboards in Practice 46Summary 47Chapter 2: The Initial High-Level Overview Tests 50The Data Profile 51The Histogram 56The Periodic Graph 58Descriptive Statistics 60Preparing the Data Profile Using Excel 62Preparing the Data Profile Using Access 64Preparing the Histogram in Excel and Access 68Preparing the Histogram in IDEA and Tableau 72Preparing the Periodic Graph in Excel and Access 74Summary 76Chapter 3: Benford's Law: The Basic Tests 79An Overview of Benford's Law 80Some Early Discussions of Benford's Law 83Selected Articles from the Eighties 85Selected Articles from the Nineties 88Scenarios Under Which Data Should Conform to Benford 90The Two Scenarios Under Which Accounting Data Sets Should Conform to Benford 93Other Considerations for the Conformity of Accounting Data 94Accounting Data Examples 95Preparing the Benford Graph Using Excel 98Preparing the Benford Graph Using Access 99Summary 101Chapter 4: Benford's Law: Advanced Topics 103Conformity and the Likelihood of Material Errors 103The First Digits Versus the First-Two Digits 107Measuring Conformity Using the Z-Statistic 109The Chi-Square and the Kolmogorov-Smirnoff Tests of Conformity 111The Mean Absolute Deviation (MAD) Test 112The Effect of Data Set Size of Conformity to Benford 114Using Benford's Law in a Forensic Accounting Setting 116Using Benford's Law for Journal Entries in an External Audit 119Using Benford for Subsidiary Ledger Balances in an External Audit 123Preparing the Benford Graph in Excel 125Summary 126Chapter 5: Benford's Law: Completing The Cycle 127The Number Duplication Test 127The Number Duplications in Accounting Textbooks 132The Electric Utility Company Fraud Case 134The Petty Cash Fraud Scheme 136The Last-Two Digits Test 139The Fraudulent Credit Card Sales Scheme 141The Missing Cash Sales Case 142Running the Number Duplication Test in Excel 144Running the Number Duplication Test in Access 146Running the Last-Two Digits Test in Excel 148Running the Last-Two Digits Test in Access 149Running the Number Duplication Test in R 151Summary 153Chapter 6: Identifying Anomalous Outliers: Part 1 154The Summation Test 155The Fraud That Was Red Flagged by Two Qualitative Outliers 158The Largest Subsets Test 161The Largest Subset Growth Test 165The School District Transportation Fraud 168The SkyBonus Fraud Scheme 170Running the Summation Test in Excel 170Running the Summation Test in Access 171Running the Largest Subsets Test in Excel 172Running the Largest Subsets Test in Access 173Running the Largest Growth Test in Excel 174Running the Largest Growth Test in Access 176Running the Largest Subsets Test in R 179Summary 180Chapter 7: Identifying Anomalous Outliers: Part 2 182Examples of Relative Size Factor Test Findings 184The Scheme That Used a Vault That Was Over Capacity 186The Scheme That Added Sold Cars to the Car Inventory Account 189The Vice Chairman of the Board Who Stole 0.5 Percent of His Salary 193Running the RSF Test in Excel 194Running the RSF Test in Access 199Running the RSF Test in SAS 208Summary 212Chapter 8: Identifying Abnormal Duplications 214The Same-Same-Same Test 215Duplicate Payments and Various Types of Fraud 217The Same-Same-Different (Near-Duplicates) Test 220The Near-Duplicates Fraud Scheme: Introduction 221The Near-Duplicates Fraud: The Act 222The Near-Duplicates Fraud: Getting the Legal Process Started 224The Near-Duplicates Fraud: Two Sentencing Hearings 228The Near-Duplicates Fraud: Epilogue 230The Subset Number Duplication Test 231Running the Same-Same-Same Test in Excel 233Running the Same-Same-Different Test in Excel 235Running the Subset Number Frequency Test in Excel 237Running the Same-Same-Same Test in Access 239Running the Same-Same-Different Test in Access 240Running the Subset Number Frequency Test in Access 242Summary 245Chapter 9: Comparing Current Period and Prior Period Data: Part 1 247A Review of Descriptive Statistics 249An Analysis of the Purchasing Card Data 250My Law: An Analysis of Payroll Data 255An Analysis of Machine Learning Data 257An Analysis of Grocery Store Sales 261The Scheme That Used Bank Transfers to a Secret Bank Account 263Running the Descriptive Statistics Tests in Excel 268Running the Descriptive Statistics Tests in Minitab 269Running the Descriptive Statistics Tests in SAS 270Summary and Discussion 272Chapter 10: Comparing Current Period and Prior Period Data: Part 2 274Vectors and Measures of Change 275An Analysis of the Purchasing Card Data 280Taxpayer Identity Theft Refund Fraud 282The Tax Return That Omitted a Million Dollar Prize 284The Tax Returns for 2000 and 2001 285The Indictment for Tax Evasion 291The Tax Evasion Trial 292The Verdict and Sentencing 298An Analysis of Joe Biden's Tax Returns 299Running the VVS Test in SAS 303Summary and Discussion 304Chapter 11: Identifying Anomalies In Time-Series Data 306An Analysis of the Purchasing Card Data 307Using IDEA for Time-Series Analysis 311The Fraud Scheme That Withdrew Funds from Customer Accounts 312Employee Data Access After Termination 317A Time-Series Analysis of Grocery Store Sales 321Using Correlation to Detect Fraud and Errors 322Using the Angle theta on Trial Balance Data 324Using the VVS on Customer Rebates 327Showing the VVS Results in a Dashboard 332Running Time-Series Analysis in SAS 334Summary and Discussion 336Chapter 12: Scoring Forensic Units for Fraud Risk 338An Overview of Risk Scoring 339The Audit Selection Method of the IRS 340The Fraudulent Vendor with a Post Office Box in the Head Office 344Risk Scoring to Detect Vendor Fraud 348Risk Scoring to Detect Errors in Sales Reports 354The Predictors Used in the Sales Report Scoring Model 356The Results of the Sales Report Scoring Model 364Summary and Discussion 365Chapter 13: Case Study: An Employee's Fraudulent Tax Refunds 367Background Information 368The Nicest Person in the Office 369The Early Years of Tax Refund Fraud Scheme 372The Later Years of Tax Refund Fraud Scheme 375An Analysis of the Fraudulent Refund Amounts 376The End Was Nigh 383The Letter of the Law 386Sentencing 391Mary Ayers-Zander 392Epilogue 393Appendix 13A: The Fraudulent Refunds 394Chapter 14: Case Study: A Supplier's Fraudulent Shipping Claims 401Background Information 401The Fraudulent Shipping Charges Scheme 403An Analysis of the Shipping Charges 405Charlene's Lifestyle 408The Scheme is Discovered 409The Corley Plea 412Charlene's Appeal for a Reduced Sentence 415The Government's Response to Charlene's Memorandum 417The Sentencing Hearing 417The Sentence 419Motion to Delay the Prison Term 420Conclusions 423Chapter 15: Detecting Financial Statement Fraud 425An Overview of Financial Statement Fraud 426Biases in Financial Statement Numbers 427Enron's Financial Statements 430Enron's Chief Financial Officer 432HealthSouth's Financial Statements 433WorldCom's Financial Statements 436WorldCom's Rounded Numbers 440Using Benford's Law to Detect Financial Statement Misconduct 442Beneish's M-Score 446Detection and Investigation Steps 447Detecting Manipulations in Monthly Subsidiary Reports 449Summary 454Chapter 16: Using Microsoft Access and R For Analytics 455An Introduction to Access 456The Architecture of Access 457A Review of Access Tables 459Importing Data into Access 461A Review of Access Queries 462Converting Excel Data into a Usable Access Format 465Using the Access Documenter 466Database Limit of 2 GB 468Reports 469Miscellaneous Access Notes 471An Introduction to R 472Installing R and R Studio 472The Advantages of Using R 474R Markdown 475Running Arithmetic Code in R 475Calculating the VVS in R 477Summary 479Appendix 16A: A Discussion of the Basic Commands 480Chapter 17: Concluding Notes on Fraud Prevention and Detection 482The Annual Cost of Employee Fraud 483The Legal Process 484"I'm a Lawyer, Trust [Account] Me" 485The Rights of the Defendant 487Possible Defenses Against an Embezzlement Charge 490The Economics of Crime Model 492Internal Controls 493Fraud Risk Assessments 495Detective Controls 496Crime Insurance 498Fraud Detection Methods 500Other Fraud Prevention Methods 501Final Words 504Bibliography 507Index 515

O autorze

MARK J. NIGRINI, PHD, is a professor at West Virginia University where he teaches highly-rated, graduate-level accounting technology and forensic accounting classes. He has published extensively in academic and professional journals on various topics related to forensic analytics. His current research addresses forensic and continuous monitoring techniques and advanced theoretical work on Benford's Law.