Gee Fraud and Fraud Detection

A Data Analytics Approach
1. Auflage 2014
ISBN: 978-1-118-77966-8
Verlag: John Wiley & Sons
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 352 Seiten, E-Book

Reihe: Wiley Corporate F&A

Detect fraud faster--no matter how well hidden--withIDEA automation
Fraud and Fraud Detection takes an advanced approach tofraud management, providing step-by-step guidance on automatingdetection and forensics using CaseWare's IDEA software. The bookbegins by reviewing the major types of fraud, then details thespecific computerized tests that can detect them. Readers willlearn to use complex data analysis techniques, including automationscripts, allowing easier and more sensitive detection of anomaliesthat require further review. The companion website provides accessto a demo version of IDEA, along with sample scripts that allowreaders to immediately test the procedures from the book.
Business systems' electronic databases have grown tremendouslywith the rise of big data, and will continue to increase atsignificant rates. Fraudulent transactions are easily hidden inthese enormous datasets, but Fraud and Fraud Detection helpsreaders gain the data analytics skills that can bring theseanomalies to light. Step-by-step instruction and practical adviceprovide the specific abilities that will enhance the audit andinvestigation process. Readers will learn to:
* Understand the different areas of fraud and their specificdetection methods
* Identify anomalies and risk areas using computerizedtechniques
* Develop a step-by-step plan for detecting fraud through dataanalytics
* Utilize IDEA software to automate detection and identificationprocedures
The delineation of detection techniques for each type of fraudmakes this book a must-have for students and new fraud preventionprofessionals, and the step-by-step guidance to automation andcomplex analytics will prove useful for even experienced examiners.With datasets growing exponentially, increasing both the speed andsensitivity of detection helps fraud professionals stay ahead ofthe game. Fraud and Fraud Detection is a guide to moreefficient, more effective fraud identification.

Autoren/Hrsg.

Gee, Sunder

Inhaltsverzeichnis

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

Über Autor(innen)

SUNDER GEE spent much of his career at the Canada RevenueAgency, including holding the position of Electronic Commerce AuditAdvisor for the Head Office. He has advised tax authorities aroundthe world on the topic of computer-assisted audit techniques(CAAT). Sunder has prepared widely respected corporate trainingmaterial and college courses on forensic accounting,anti-money laundering, and data analytics.