Description
Book SynopsisUncover hidden fraud and red flags using efficient data analytics 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 audi
Table of Contents
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
