Fraud and Fraud Detection (eBook)

A Data Analytics Approach

Sunder Gee (Autor)

eBook Download: PDF

2014
John Wiley & Sons (Verlag)
978-1-118-77967-5 (ISBN)

Infos

Detect fraud faster no matter how well hidden with IDEA automation Fraud and Fraud Detection takes an advanced approach to fraud management, providing step-by-step guidance on automating detection and forensics using CaseWare's IDEA software. The book begins by reviewing the major types of fraud, then details the specific computerized tests that can detect them. Readers will learn to use complex data analysis techniques, including automation scripts, allowing easier and more sensitive detection of anomalies that require further review. The companion website provides access to a demo version of IDEA, along with sample scripts that allow readers to immediately test the procedures from the book. Business systems' electronic databases have grown tremendously with the rise of big data, and will continue to increase at significant rates. Fraudulent transactions are easily hidden in these enormous datasets, but Fraud and Fraud Detection helps readers gain the data analytics skills that can bring these anomalies to light. Step-by-step instruction and practical advice provide the specific abilities that will enhance the audit and investigation process. Readers will learn to: Understand the different areas of fraud and their specific detection methods Identify anomalies and risk areas using computerized techniques Develop a step-by-step plan for detecting fraud through data analytics Utilize IDEA software to automate detection and identification procedures The delineation of detection techniques for each type of fraud makes this book a must-have for students and new fraud prevention professionals, and the step-by-step guidance to automation and complex analytics will prove useful for even experienced examiners. With datasets growing exponentially, increasing both the speed and sensitivity of detection helps fraud professionals stay ahead of the game. Fraud and Fraud Detection is a guide to more efficient, more effective fraud identification.

Autor

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

Inhalt

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

Produkt-Details

• Erscheint lt. Verlag: 5.11.2014
• Reihe/Serie: Wiley Corporate F&A
• Reihe/Serie: Wiley Corporate F&A
• Reihe/Serie: Wiley Corporate F&A
• Sprache: englisch
• Themenwelt: Recht / Steuern ► Strafrecht ► Kriminologie
• Themenwelt: Sozialwissenschaften
• Themenwelt: Wirtschaft ► Betriebswirtschaft / Management ► Finanzierung
• Themenwelt: Wirtschaft ► Betriebswirtschaft / Management ► Rechnungswesen / Bilanzen
• Schlagworte: Accounting • Accounting Technology • advanced fraud detection • automated anomaly detection • automated fraud detection • big data fraud • Bilanzdelikt • CaseWare • computerized fraud detection • Data Integrity • electronic suppression of sales • faster fraud detection • File Formats • forensic accounting techniques • Forensic Analytics • Fraud and Fraud Detection: A Data Analytics Approach • Fraud Auditing • fraud data analytics • fraud detection software • fraud detection techniques • fraud identification • fraud investigation • Idea • IDEA automation scripts • IDEA forensics • IDEA fraud detection • large dataset fraud • obtaining large datasets • occupational fraud • phantom-ware • POS • Rechnungswesen • Rechnungswesen / Technologie • sensitive fraud detection • statistics and sampling for auditors and accountants • Sunder Gee • zappers
• ISBN-10: 1-118-77967-3 / 1118779673
• ISBN-13: 978-1-118-77967-5 / 9781118779675