Fraud Data Analytics Methodology

Fraud Data Analytics Methodology addresses the need for clear, reliable fraud detection with a solid framework for a robust data analytic plan. By combining fraud risk assessment and fraud data analytics, you'll be able to better identify and respond to the risk of fraud in your audits. Proven techniques help you identify signs of fraud hidden deep within company databases, and strategic guidance demonstrates how to build data interrogation search routines into your fraud risk assessment to locate red flags and fraudulent transactions. These methodologies require no advanced software skills, and are easily implemented and integrated into any existing audit program. Professional standards now require all audits to include data analytics, and this informative guide shows you how to leverage this critical tool for recognizing fraud in today's core business systems.

Fraud cannot be detected through audit unless the sample contains a fraudulent transaction. This book explores methodologies that allow you to locate transactions that should undergo audit testing.

• Locate hidden signs of fraud
• Build a holistic fraud data analytic plan
• Identify red flags that lead to fraudulent transactions
• Build efficient data interrogation into your audit plan

Incorporating data analytics into your audit program is not about reinventing the wheel. A good auditor must make use of every tool available, and recent advances in analytics have made it accessible to everyone, at any level of IT proficiency. When the old methods are no longer sufficient, new tools are often the boost that brings exceptional results. Fraud Data Analytics Methodology gets you up to speed, with a brand new tool box for fraud detection.

Preface ix

Acknowledgments xi

Chapter 1: Introduction to Fraud Data Analytics 1

Chapter 2: Fraud Scenario Identification 17

Chapter 3: Data Analytics Strategies for Fraud Detection 41

Chapter 4: How to Build a Fraud Data Analytics Plan 81

Chapter 5: Data Analytics in the Fraud Audit 109

Chapter 6: Fraud Data Analytics for Shell Companies 127

Chapter 7: Fraud Data Analytics for Fraudulent Disbursements 149

Chapter 8: Fraud Data Analytics for Payroll Fraud 183

Chapter 9: Fraud Data Analytics for Company Credit Cards 205

Chapter 10: Fraud Data Analytics for Theft of Revenue and Cash Receipts 227

Chapter 11: Fraud Data Analytics for Corruption Occurring in the Procurement Process 247

Chapter 12: Corruption Committed by the Company 269

Chapter 13: Fraud Data Analytics for Financial Statements 285

Chapter 14: Fraud Data Analytics for Revenue and Accounts Receivable Misstatement 311

Chapter 15: Fraud Data Analytics for Journal Entries 333

Appendix A: Data Mining Audit Program for Shell Companies 349

About the Author 363

Index 365

LEONARD W. VONA, CPA, CFE, is the CEO of Fraud Auditing and a world-renowned authority in fraud auditing. He has provided expert witness testimony in federal and state courts; consulted with corporations around the world; and is the author of Fraud Risk Assessment: Building the Fraud Audit Program and The Fraud Audit: Responding to the Risk of Fraud in Core Business Systems, both published by Wiley. A forensic auditor with more than 38 years of diversified forensic auditing experience, he has provided more than 1,500 days of fraud training around the world.

Fraud doesn't stand out within millions of transactions. To further complicate matters, every data anomaly isn't necessarily fraud. To be successful at fraud data analytics, you must develop a skillful balance of hard science and practiced art to see the suspect scenarios like watermarks in the spreadsheets. Fraud Data Analytics Methodology lays out a convenient, detailed collection of the most common fraud scenarios and how they manifest in every core business system.

Written by a financial investigator with more than thirty years of practice, including extensive trial experience in state and federal courts, this guiding reference offers a step-by-step fraud data analytics methodology for effectively analyzing data with a goal of selecting transactions for audit examination. It opens with a straightforward primer on fraud data analytics to give you everything you need to understand and use the covered approach. From creating fraud scenarios to writing the fraud data analytics plan to the strategies for identifying red flags, comprehensive coverage is easily accessible and requires no advanced software skills. Every chapter includes a summary of critical points to remember for quick reference and a list of the most common pitfalls to avoid. While you may not always know the type of fraud being committed, this methodology ensures you find and identify every variation of fraud scenario by:

• Thoroughly demonstrating how to use fraud data analytics to uncover asset misappropriation, corruption, and financial reporting schemes, including how the fraud scenario correlates to each phase of the audit
• Providing direction on how and when to use specific strategies, along with guidance on locating fraud scenarios at all levels of concealment
• Nailing down the ten key questions to answer when creating a fraud data analytics audit program, and the eight-step process for customizing a data interrogation routine to locate fraud scenarios

Perpetrators always leave a trail of their crimes in your data systems, and Fraud Data Analytics Methodology is your surefire way to find them.

Praise for FRAUD DATA ANALYTICS METHODOLOGY

"Leonard Vona inspired my fraud career and introduced me to the incredible power of data analytics in detecting and fighting fraud. His new book is sure to inspire many more fraud fighters. His clear and concise guidance and instruction will provide even new fraud fighters powerful techniques that are certain to deliver results."
—Mary Breslin, CIA, CFE, President, Empower Audit Training and Consulting

"Leonard's emphasis to first seek to understand how fraud can happen and only then create and carry-out fraud data analytics and procedures should maximize internal audit's impact, while minimizing time spent on engagement planning. This book provides detailed instructions on how to audit for fraud for all key business processes and should be leveraged by all serious Internal Auditors."
—Tom O'Reilly, Vice President and General Manager of Internal Audit and Seminars, MIS Training Institute

"Fraud Data Analytics Methodology will help auditors close the expectation gap. It is an in-depth manual for using a fraud scenario approach to finding just about any kind of fraud. The author provides step-by-step guidance on fraud planning reports and analytics that will detect fraudulent transactions within a company's business systems."
—Carolyn J. Newman, President, Audimation Services, Inc.– A CaseWare Analytics Partner

"I recommend this book to auditors who want to look for fraud in a structured, methodical and scientific way."
—Hassan Mohd. Ali Al Lawati, Assistant Chief Internal Auditor, Oman LNG