Fraud and Fraud Detection: A Data Analytics Approach
By Sunder Gee
Description
Business databases have grown tremendously with the rise of big data and will continue to expand at significant rates. Fraudulent transactions are easily hidden in these enormous datasets, but this book helps you gain the data analytics skills that can be used in conjunction with any analytics software in order to bring these anomalies to light.
"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 (demo version included on companion website).
You will discover how 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
Product Details
Label | Value |
---|---|
ISBN | 978-1-118-77965-1 |
Publisher | Wiley; 1 Edition (December 3, 2014) |
Published | Copyright 2015 |
Pages | 352 |
Format | Hardcover |
Table of Contents
Chapter 1 | Introduction |
---|---|
Chapter 2 | Fraud Detection |
Chapter 3 | The Data Analysis Cycle |
Chapter 4 | Statistics and Sampling |
Chapter 5 | Data Analytical Tests |
Chapter 6 | Advanced Data Analytical Tests |
Chapter 7 | Skimming and Cash Larceny |
Chapter 8 | Billing Schemes |
Chapter 9 | Check-Tampering Schemes |
Chapter 10 | Payroll Fraud |
Chapter 11 | Expense Reimbursement Schemes |
Chapter 12 | Register Disbursement Schemes |
Chapter 13 | Noncash Misappropriations |
Chapter 14 | Corruption |
Chapter 15 | Money Laundering |
Chapter 16 | Zapper Fraud |
Chapter 17 | Automation and IDEAScript |
Chapter 18 | Conclusion |
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