Fraud and Fraud Detection

Preface
Acknowledgments
Chapter 1: Introduction
Defining Fraud
Anomalies versus Fraud
Types of Fraud
Assess the Risk of Fraud
Conclusion
Notes
Chapter 2: Fraud Detection
Recognizing Fraud
Data Mining versus Data Analysis and Analytics
Data Analytic Software
Anomalies versus Fraud within Data
Fraudulent Data Inclusions and Deletions
Conclusion
Notes
Chapter 3: The Data Analysis Cycle
Evaluating and Analysis
Obtaining Data Files
File Format Types
Preparation for Data Analysis
Arranging and Organizing Data
Conclusion
Notes
Chapter 4: Statistics and Sampling
Descriptive Statistics
Inferential Statistics
Measures of Center
Measure of Dispersion
Measure of Variability
Sampling
Conclusion
Notes
Chapter 5: Data Analytical Tests
Benford's Law
Number Duplication Test (NDT)
Z- Score
Relative Size Factor Test (RSF)
Same - Same - Same Test (SSS)
Same - Same - Different Test (SSD)
Even Amounts
Conclusion
Notes
Chapter 6: Advanced Data Analytical Tests
Correlation
Trend Analysis
GEL - 1 and GEL -2
Conclusion
Note
Chapter 7: Skimming and Cash Larceny
Skimming
Cash Larceny
Case Study
Conclusion
Chapter 8: Billing Schemes
Data and Data Familiarization
Benford's Law Tests
Relative Size Factor Test
Z-Score
Even Dollar Amounts
Same-Same-Same Test
Same-Same-Different Test
Payments without Purchase Orders Test
Length of Time between Invoice and Payment Dates Test
Search for Post Office Box
Match Employee Address to Supplier
Duplicate addresses in Vendor Master
Payments to vendors not in Master
Gap Detection of Cheque number sequences
Conclusion
Note
Chapter 9: Cheque Tampering Schemes
Electronic Payments Fraud Prevention
Cheque Tampering
Data Analytic Tests
Conclusion
Chapter 10: Payroll Fraud
Data and Data Familiarization
Data Analysis
The Payroll Register
Payroll Master and Commission Tests
Conclusion
Notes
Chapter 11: Expense Reimbursement Schemes
Data and Data Analysis
Conclusion and Audit Trail
Notes
Chapter 12: Register Disbursement Schemes
False Refunds and Adjustments
False Voids
Concealment
Data Analytic Tests
Conclusion
Chapter 13: Non-Cash Misappropriations
Types of Non-Cash Misappropriations
Concealment of Non-Cash Misappropriations
Data Analytics
Conclusion
Chapter 14: Corruption
Bribery
Tender Schemes
Kickbacks, Illegal Gratuities and Extortion
Conflict of Interest
Data Analytic Tests
Concealment
Conclusion
Chapter 15: Money Laundering
The Money Laundering Process
Other Money Transfer Systems and New Opportunities
Audit Areas and Data Files
Conclusion
Notes
Chapter 16: Zapper Fraud
Point of Sales System Case Study
Quantifying the Zapped Records
Additional POS Data Files to Analyse
Missing and Modified Bills
The Mark-up Ratios
Conclusions and Solutions
Notes
Chapter 17: Automation and IDEAScript
Considerations for Automation
Creating IDEAScripts
Conclusion
Chapter 18: Conclusion
Financial Statement Fraud
IDEA Features Demonstrated
Projects Overview
Data Analytics: Final Words
Notes
About the Companion Website
About the Author
Index