Book description
Proven guidance for expertly using analytics in fraud examinations, financial analysis, auditing and fraud prevention
Fraud Analytics thoroughly reveals the elements of analysis that are used in today's fraud examinations, fraud investigations, and financial crime investigations. This valuable resource reviews the types of analysis that should be considered prior to beginning an investigation and explains how to optimally use data mining techniques to detect fraud. Packed with examples and sample cases illustrating pertinent concepts in practice, this book also explores the two major data analytics providers: ACL and IDEA.
Looks at elements of analysis used in today's fraud examinations
Reveals how to use data mining (fraud analytic) techniques to detect fraud
Examines ACL and IDEA as indispensable tools for fraud detection
Includes an abundance of sample cases and examples
Written by Delena D Spann, Board of Regent (Emeritus) for the Association of Certified Fraud Examiners (ACFE), who currently serves as Advisory Board Member of the Association of Certified Fraud Examiners, Board Member of the Education Task Force of the Association of Certified Anti-Money Laundering Specialists ASIS International (Economic Crime Council) and Advisory Board Member of the Robert Morris University (School of Business), Fraud Analytics equips you with authoritative fraud analysis techniques you can put to use right away.
Table of contents
- Cover Page
- Title Page
- Copyright
- Dedication
- Contents
- Foreword
- Preface
- Acknowledgments
- Chapter 1: The Schematics of Fraud and Fraud Analytics
- Chapter 2: The Evolution of Fraud Analytics
- Chapter 3: The Analytical Process and the Fraud Analytical Approach
- Chapter 4: Using ACL Analytics in the Face of Excel
-
Chapter 5: Fraud Analytics versus Predictive Analytics
- OVERVIEW OF FRAUD ANALYSIS AND PREDICTIVE ANALYSIS
- COMPARING AND CONTRASTING METHODOLOGIES
- 13 STEP SCORE DEVELOPMENT VERSUS FRAUD ANALYSIS
- CRISP-DM VERSUS FRAUD DATA ANALYSIS
- SAS/SEMMA VERSUS FRAUD DATA ANALYSIS
- CONFLICTS WITHIN METHODOLOGIES
- COMPOSITE METHODOLOGY
- COMPARING AND CONTRASTING PREDICTIVE MODELING AND DATA ANALYSIS
- NOTES
- Chapter 6: CaseWare IDEA Data Analysis Software
- Chapter 7: Centrifuge Analytics: Is Big Data Enough?
- Chapter 8: i2 Analyst's Notebook: Best in Fraud Solutions
- Chapter 9: The Power to Know Big Data:
- Chapter 10: New Trends in Fraud Analytics and Tools
- About the Author
- Index
Product information
- Title: Fraud Analytics: Strategies and Methods for Detection and Prevention
- Author(s):
- Release date: October 2013
- Publisher(s): Wiley
- ISBN: 9781118230688
You might also like
book
Financial Statement Fraud: Strategies for Detection and Investigation
Valuable guidance for staying one step ahead of financial statement fraud Financial statement fraud is one …
book
Financial Fraud Prevention and Detection: Governance and Effective Practices
Step-by-step guidance for board members and executives on preventing and detecting accounting fraud In the wake …
book
Money Laundering Prevention: Deterring, Detecting, and Resolving Financial Fraud
A how-to guide for the discovery and prevention of the illegal transfer of money Written for …
book
Fraud Data Analytics Methodology
Uncover hidden fraud and red flags using efficient data analytics Fraud Data Analytics Methodology addresses the …