Fraud and Fraud Detection E-Book

Sunder Gee

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Serie: Wiley Corporate F&A
• Sprache: Englisch

Seitenzahl: 479

Veröffentlichungsjahr: 2014

Beschreibung

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.

Leseprobe

The Wiley Corporate F&A series provides information, tools, and insights to corporate professionals responsible for issues affecting the profitability of their company, from accounting and finance to internal controls and performance management.

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Fraud and Fraud Detection

A Data Analytics Approach

SUNDER GEE

Cover image: ©iStock.com/Mr.Vi Cover design: Wiley

Copyright © 2015 by Sunder Gee. All rights reserved.

Published by John Wiley & Sons, Inc., Hoboken, New Jersey.

Published simultaneously in Canada.

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Library of Congress Cataloging-in-Publication Data:

Gee, Sunder.     Fraud and fraud detection : a data analytics approach/Sunder Gee.         pages cm. — (Wiley corporate F&A series)     Includes index.     ISBN 978-1-118-77965-1 (hardback) — ISBN 978-1-118-77967-5 (ePDF) — ISBN 978-1-118-77966-8 (ePub) — ISBN 978-1-118-93676-4 (oBook) 1. Fraud. 2. Managerial accounting. 3. Data mining. I. Title.     HV6691.G44 2014     658.4′73—dc23

2014021352

Contents

Foreword

Preface

HOW THIS BOOK IS ORGANIZED

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 ANALYTICAL SOFTWARE

ANOMALIES VERSUS FRAUD WITHIN DATA

FRAUDULENT DATA INCLUSIONS AND DELETIONS

CONCLUSION

NOTES

CHAPTER 3 The Data Analysis Cycle

EVALUATION AND ANALYSIS

OBTAINING DATA FILES

PERFORMING THE AUDIT

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

Z-SCORE

RELATIVE SIZE FACTOR TEST

SAME-SAME-SAME TEST

SAME-SAME-DIFFERENT TEST

EVEN AMOUNTS

CONCLUSION

NOTES

CHAPTER 6 Advanced Data Analytical Tests

CORRELATION

TREND ANALYSIS

GEL-1 AND GEL-2

CONCLUSION

NOTES

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 CHECK NUMBER SEQUENCES

CONCLUSION

NOTES

CHAPTER 9 Check-Tampering Schemes

ELECTRONIC PAYMENTS FRAUD PREVENTION

CHECK TAMPERING

DATA ANALYTICAL 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 ANALYTICAL TESTS

CONCLUSION

CHAPTER 13 Noncash Misappropriations

TYPES OF NONCASH MISAPPROPRIATIONS

CONCEALMENT OF NONCASH MISAPPROPRIATIONS

DATA ANALYTICS

CONCLUSION

CHAPTER 14 Corruption

BRIBERY

TENDER SCHEMES

KICKBACKS, ILLEGAL GRATUITIES, AND EXTORTION

CONFLICT OF INTEREST

DATA ANALYTICAL TESTS

CONCEALMENT

CONCLUSION

CHAPTER 15 Money Laundering

THE MONEY-LAUNDERING PROCESS

OTHER MONEY TRANSFER SYSTEMS AND NEW OPPORTUNITIES

AUDIT AREAS AND DATA FILES

CONCLUSION

CHAPTER 16 Zapper Fraud

POINT-OF-SALES SYSTEM CASE STUDY

QUANTIFYING THE ZAPPED RECORDS

ADDITIONAL POS DATA FILES TO ANALYZE

MISSING AND MODIFIED BILLS

THE MARKUP 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 Author

About the Website

Index

End User License Agreement

List of Tables

Chapter 5

Table 5.1

Table 5.2

Chapter 16

Table 16.1

Table 16.2

Table 16.3

Table 16.4

Table 16.5

List of Illustrations

Chapter 1

Figure 1.1

Occupational Fraud and Abuse Classification System

Chapter 3

Figure 3.1

Arbutus Analyzer ODBC Data Import

Figure 3.2

Arbutus Analyzer Data Import by Arbutus Software Inc.

Figure 3.3

IDEA Data Import Assistant by CaseWare IDEA Inc.

Figure 3.4

Payment Tender Type File Example in IDEA

Figure 3.5

Field Statistics of the Payment Tender File

Figure 3.6

Isolating the Field Statistics of the Payment Amount

Figure 3.7

Date Field Statistics

Figure 3.8

Time Field Statistics

Figure 3.9

Summarization of Payment Tender Types

Figure 3.10

Summarization of Tender Type Results

Figure 3.11

Stratification of Payment Amounts by Tender Types

Figure 3.12

Results of the Stratification for Debit Card Payments

Figure 3.13

Results of the Stratification for Cash Payments

Figure 3.14

Creating a Pivot Table View and Results

Figure 3.15

Direct File Extraction of Each Payment Tender Type

Figure 3.16

Using IDEA’s Visual Connector to Join the Payment Tender Type Files

Figure 3.17

Resulting Tender Master File with Each Tender Type in Individual Columns

Chapter 4

Figure 4.1

Nonstatistical Sampling Feature in IDEA

Figure 4.2

Applying Random Record Sampling in IDEA

Figure 4.3

Output of Random Sampling

Figure 4.4

Applying Systematic Record Sampling

Figure 4.5

Selecting the Ranges for Stratified Random Sampling

Figure 4.6

Selecting the Number of Records to Sample in Stratified Random Sampling

Figure 4.7

Monetary Unit Sampling Feature

Figure 4.8

Monetary Unit Sampling Planning

Figure 4.9

Extracting the Sample Records for Monetary Unit Sampling

Figure 4.10

Random Record Selection Results for Monetary Unit Sampling

Figure 4.11

Audit Results of the Sampled Records