You are previewing Fraud Analytics: Strategies and Methods for Detection and Prevention.
O'Reilly logo
Fraud Analytics: Strategies and Methods for Detection and Prevention

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

    1. Cover Page
    2. Title Page
    3. Copyright
    4. Dedication
    5. Contents
    6. Foreword
    7. Preface
    8. Acknowledgments
    9. Chapter 1: The Schematics of Fraud and Fraud Analytics
      1. HOW DO WE DEFINE FRAUD ANALYTICS?
      2. MINING THE FIELD: FRAUD ANALYTICS IN ITS NEW PHASE
      3. HOW DO WE USE FRAUD ANALYTICS?
      4. FRAUD DETECTION
      5. HOW DO WE DEFINE FRAUD ANALYTICS?
      6. FRAUD ANALYTICS REFINED
      7. NOTES
    10. Chapter 2: The Evolution of Fraud Analytics
      1. WHY USE FRAUD ANALYTICS?
      2. THE EVOLUTION CONTINUES
      3. FRAUD PREVENTION AND DETECTION IN FRAUD ANALYTICS
      4. INCENTIVES, PRESSURES, AND OPPORTUNITIES
      5. NOTES
    11. Chapter 3: The Analytical Process and the Fraud Analytical Approach
      1. THE TURN OF THE ANALYTICAL WHEEL
      2. IT TAKES MORE THAN ONE STEP
      3. PROBABILITIES OF FRAUD AND WHERE IT ALL BEGINS
      4. WHAT SHOULD THE FRAUD ANALYTICS PROCESS LOOK LIKE?
      5. DATA ANALYTICS EXPOSED
      6. NOTES
    12. Chapter 4: Using ACL Analytics in the Face of Excel
      1. THE DEVIL REMAINS IN THE DETAILS
      2. NOTES
    13. Chapter 5: Fraud Analytics versus Predictive Analytics
      1. OVERVIEW OF FRAUD ANALYSIS AND PREDICTIVE ANALYSIS
      2. COMPARING AND CONTRASTING METHODOLOGIES
      3. 13 STEP SCORE DEVELOPMENT VERSUS FRAUD ANALYSIS
      4. CRISP-DM VERSUS FRAUD DATA ANALYSIS
      5. SAS/SEMMA VERSUS FRAUD DATA ANALYSIS
      6. CONFLICTS WITHIN METHODOLOGIES
      7. COMPOSITE METHODOLOGY
      8. COMPARING AND CONTRASTING PREDICTIVE MODELING AND DATA ANALYSIS
      9. NOTES
    14. Chapter 6: CaseWare IDEA Data Analysis Software
      1. DETECTING FRAUD WITH IDEA
      2. FRAUD ANALYSIS POINTS OF IDEA
      3. CORRELATION, TREND ANALYSIS, AND TIME SERIES ANALYSIS
      4. WHAT IS IDEA'S PURPOSE?
      5. A SIMPLE SCHEME: THE PURCHASE FRAUD OF AN EMPLOYEE AS A VENDOR
      6. STAGES OF USING IDEA
      7. NOTES
    15. Chapter 7: Centrifuge Analytics: Is Big Data Enough?
      1. SOPHISTICATED LINK ANALYSIS
      2. THE CHALLENGE WITH ANTI-COUNTERFEITING
      3. INTERACTIVE ANALYTICS: THE CENTRIFUGE WAY
      4. FRAUD ANALYSIS WITH CENTRIFUGE VNA
      5. THE FRAUD MANAGEMENT PROCESS
      6. NOTES
    16. Chapter 8: i2 Analyst's Notebook: Best in Fraud Solutions
      1. RAPID INVESTIGATION OF FRAUD AND FRAUDSTERS
      2. i2 ANALYST'S NOTEBOOK
      3. i2 ANALYST'S NOTEBOOK AND FRAUD ANALYTICS
      4. HOW TO USE i2 ANALYST'S NOTEBOOK: FRAUD FINANCIAL ANALYTICS
      5. USING i2 ANALYST'S NOTEBOOK IN A MONEYLAUNDERING SCENARIO
      6. NOTES
    17. Chapter 9: The Power to Know Big Data:
      1. THE SAS WAY
      2. ACTIONABLE INTELLIGENCE TECHNOLOGIES' FINANCIAL INVESTIGATIVE SOFTWARE
      3. A CASE IN POINT
      4. NOTES
    18. Chapter 10: New Trends in Fraud Analytics and Tools
      1. THE MANY FACES OF FRAUD ANALYTICS
      2. THE PAPER CHASE IS OVER
      3. TO BE OR NOT TO BE
      4. RAYTHEON'S VISUALINKS
      5. FICO INSURANCE FRAUD MANAGER 3.3
      6. IBM i2 iBase
      7. PALANTIR TECH
      8. FISERV'S AML MANAGER
      9. NOTES
    19. About the Author
    20. Index