Using Analytics to Detect Possible Fraud

Detailed tools and techniques for developing efficiency and effectiveness in forensic accounting

Using Analytics to Detect Possible Fraud: Tools and Techniques is a practical overview of the first stage of forensic accounting, providing a common source of analytical techniques used for both efficiency and effectiveness in forensic accounting investigations. 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.

• Shows how to develop both efficiency and effectiveness in forensic accounting
• Provides information in such a way that non-practitioners can easily understand
• Written in plain language: advanced mathematical skills are not required
• Features actual case studies using analytical tests

Essential reading for every investor who wants to prevent financial fraud, Using Analytics to Detect Possible Fraud allows practitioners to focus on areas that require further investigative techniques and to unearth deceptive financial reporting before it's too late.

Preface xi

Acknowledgments xv

Chapter 1: Overview of the Companies 1

The Four Companies 2

Company 1 2

Company 2 5

Company 3 8

Company 4 10

Summary 16

Chapter 2: The “Norm” and the “Forensic” Preliminary Analytics: Basics Everyone Should Know 19

Liquidity Ratios 20

Working Capital 21

Working Capital Index 21

Working Capital Turnover 22

Current Ratio 22

Case Studies: Liquidity Ratios 22

Profitability Ratios 25

Gross Profit 26

Gross Profit Margin 26

Stock Sales 26

Return on Equity 27

Case Studies: Profitability Ratios 27

Company 1 31

Horizontal Analysis 36

Company 1 36

Company 2 43

Company 3 50

Company 4 61

Vertical Analysis 66

Company 1 66

Company 2 70

Company 3 73

Company 4 79

Summary 79

Chapter 3: The Importance of Cash Flows and Cash Flow Statements 83

Cash Flows and Net Income 85

Company 1 87

Company 2 89

Company 3 92

Company 4 97

Other Cash Flow Techniques 100

Company 1 101

Company 2 104

Company 3 107

Company 4 114

Summary 117

Chapter 4: The Beneish M-Score Model 119

Company 1 124

Company 2 133

Company 3 143

Indices of the Primary Government 145

Indices of the Governmental Funds 151

Company 4 158

Summary 166

Notes 170

Chapter 5: The Accruals 171

Dechow–Dichev Accrual Quality 173

The Four Companies: Dechow–Dichev Model 175

Sloan’s Accruals 184

The Four Companies: Sloan’s Model 185

Jones Nondiscretionary Accruals 191

The Four Companies: Jones Model 192

Summary 196

Notes 198

Chapter 6: Analysis Techniques Using Historical Financial Statements and Other Company Information 199

The Piotroski F-Score Model 200

Company 1 203

Company 2 205

Company 3 207

Company 4 212

Lev–Thiagarajan’s 12 Signals 215

Company 1 220

Company 2 222

Company 3 225

Company 4 230

Summary 233

Notes 235

Chapter 7: Benford's Law, and Yes—Even Statistics 237

Benford’s Law 239

Company 1 243

Company 2 249

Company 3 255

Company 4 267

Simple Statistics 272

Company 1 277

Company 2 281

Company 3 284

Company 4 289

Summary 290

Note 292

Chapter 8: Grading the Four Companies 293

Company 1 294

Company 2 302

Company 3 310

Company 4 320

Summary 326

Bibliography 329

About the Author 331

Index 333

PAMELA S. MANTONE, CPA, CFF, CITP, CGMA, CFE, FCPA, is a Senior Assurance Manager at Joseph Decosimo & Company, PLLC, practicing in the areas of audit and attestation with a focus on forensic accounting, fraud examination and audits of financial institutions, nonprofit organizations, publicly traded companies and governments. She provides forensic accounting services, with an emphasis on embezzlement and fraudulent financial information for multiple organizations, as well as consulting services regarding the implementation of fraud prevention and fraud protection internal control systems.

USING ANALYTICS TO DETECT POSSIBLE FRAUD
Tools and Techniques

Forensic accounting is the hot new field in accounting, involving essential investigative techniques that uncover accounting fraud and enable practitioners to be effective in covering the needs of the engagement.

Using Analytics to Detect Possible Fraud: Tools and Techniques presents a plain-English guide to forensic accounting, providing analytical tools and techniques that allow professionals analyzing financial statements to zero in on anomalies. Certified Fraud Examiner Pamela Mantone introduces a variety of techniques starting from the very basic, simple analytics to more advanced analytical tools that equip forensic accountants, forensic investigators, and fraud investigators to develop further investigative work.

Featuring case studies throughout from four companies, illustrating the application of tools included in the book, Using Analytics to Detect Possible Fraud demonstrates how to interpret the results of the testing in each case study, with techniques including:

• Liquidity ratios
• Profitability ratios
• Horizontal analysis
• Vertical analysis
• Cash realized from operations
• Analyzing cash realized from operations to net income from operations
• The Beneish M-Score Model
• Dechow-Dichev Accrual Quality
• Sloan's Accruals
• Jones Non-discretionary Accruals
• The Piotroski F-Score Model
• Lev-Thiagarajan's 12 Signals
• Benford's Law
• Z-Score Analysis
• Correlation
• Regression Analysis

Essential reading for every financial investigator, Using Analytics to Detect Possible Fraud allows practitioners to focus on areas that require further investigative techniques and to unearth deceptive financial reporting.