Fraud and Fraud Detection

Fraud and Fraud Detection
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Описание книги

How does a CEO, manager, or entrepreneur begin to sort out what defines and drives a good customer experience and how it can be measured and made actionable? If you know how well the customer experience is satisfying your customers and you know how to increase their satisfaction, you can then increase sales, return visits, recommendations, loyalty, and brand engagement across all channels. More reliable and more useful data leads to better decisions and better results. Innovating Analytics is also about the need for a comprehensive measurement ecosystem to accurately assess and improve the other elements of customer experience. This is a time of great change and great opportunity. The companies that use the right tools and make the right assessments of how to satisfy their customers will have the competitive advantage. Innovating Analytics introduces an index that measures a customer’s likelihood to recommend and the likelihood to detract. The current concept of the Net Promoter Score (NPS) that has been adopted by many companies during the last decade—is no longer accurate, precise or actionable. This new metric called the Word of Mouth Index (WoMI) has been tested on hundreds of companies and with over 1.5 million consumers over the last two years. Author Larry Freed details the improvement that WoMI provides within what he calls the Measurement Ecosystem. He then goes on to look at three other drivers of customer satisfaction along with word of mouth: customer acquisition, customer loyalty, and customer conversion.

Оглавление

Gee Sunder. Fraud and Fraud Detection

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

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

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

CHAPTER 4. Statistics and Sampling

DESCRIPTIVE STATISTICS

INFERENTIAL STATISTICS

MEASURES OF CENTER

MEASURE OF DISPERSION

MEASURE OF VARIABILITY

SAMPLING

CONCLUSION

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

CHAPTER 6. Advanced Data Analytical Tests

CORRELATION

TREND ANALYSIS

GEL-1 AND GEL-2

CONCLUSION

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

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

CHAPTER 11. Expense Reimbursement Schemes

DATA AND DATA ANALYSIS

CONCLUSION AND AUDIT TRAIL

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

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

About the Author

About the Website

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Fraud and Fraud Detection

A Data Analytics Approach

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