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DELENA D. SPANN, MSc, CFE, is employed with the United States Secret Service, Chicago Field Office, where she is assigned to the Electronic and Financial Crimes Task Force.
Spann routinely serves on high-profile financial crimes investigations that include detecting red flags, trends, and anomalies in complex financial transactions. She is frequently called upon as a guest speaker on her expertise in fraud analytics and financial crimes. She is dedicated to the study of white-collar crime.
Spann holds a bachelor's degree in liberal studies from Barry University and a master of science degree in criminal justice administration from Florida International University. She is Board of Regent (Emeritus), an Advisory Board Member, and Higher Education Committee Member of the Association of Certified Fraud Examiners; a Board of Director of ASIS International Economic Crime Council; Education Task Force Member of the Association of Certified Anti-Money Laundering Specialists; Advisory Board Member at Robert Morris University; Executive Director of the Association of Certified Fraud Examiners, Greater Chicago Chapter; a Threat Finance Task Force Member of the Association of Certified Financial Crimes Specialists; and Board of Director (Emeritus), Step Women's Network of Chicago. Spann also serves as an adjunct professor at the university/college level.
Foreword
Preface
Acknowledgments
Chapter 1: The Schematics of Fraud and Fraud Analytics
Report to the Nations on Occupational Fraud and Abuse
Mining the Field: Fraud Analytics in Its New Phase
How Do We Use Fraud Analytics?
Fraud Detection
How Do We Define Fraud Analytics?
Fraud Analytics Refined
Notes
Chapter 2: The Evolution of Fraud Analytics
Why Use Fraud Analytics?
Case Study
The Evolution Continues
Fraud Prevention and Detection in Fraud Analytics
Incentives, Pressures, and Opportunities
Notes
Chapter 3: The Analytical Process and the Fraud Analytical Approach
The Turn of the Analytical Wheel
It Takes More than One Step
Probabilities of Fraud and Where It All Begins
What Should the Fraud Analytics Process Look Like?
Fraud Data Analytics Exposed
Notes
Chapter 4: Using ACL Analytics in the Face of Excel
Case Study: ACL Inventory Fraud of Operation Supply and Demand
The Devil Remains in the Details
Notes
Chapter 5: Fraud Analytics versus Predictive Analytics
Overview of Fraud (Data) Analytics and Predictive Analysis (Modeling)
Comparing and Contrasting Methodologies
13 Step Score Development versus Fraud Analytics
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: IDEA Data Analysis Software
Detecting Fraud with IDEA
IDEA Case Study
Fraud Analysis Points of IDEA
Correlation, Trend Analysis, and Time Series Analysis
What is IDEA’s Purpose?
A Simple Scheme: The Purchase Fraud of an Employee as a Vendor
Stages of Using IDEA
Notes
Chapter 7: Centrifuge Analytics: Is Big Data Enough?
Sophisticated Link Analysis
Centrifuge Visual Network Analytics for Anti-Counterfeiting
The Challenge with Anti-Counterfeiting
Interactive Analytics: The Centrifuge Way
Case Scenario
Fraud Analysis
The Fraud Management Process
Notes
Chapter 8 i2 Analyst Notebook: The Best in Fraud Solutions
Rapid Investigation of Fraud and Fraudsters
I2 Analyst Notebook
I2 Analyst Notebook and Fraud Analytics
How to Use i2 Analyst’s Notebook: Fraud Financial Analytics
Money Laundering and Using i2 Analyst Notebook Case Scenario and Process
Notes
Chapter 9: The Power to Know Big Data: SAS Visual Analytics and Actionable Intelligence Technology’s-Financial Intelligence System
The SAS Way
AITFIS (Actionable Intelligence Technologies Financial Investigations Systems)
Case Study Using FIS
Notes
Chapter 10: New Trends in Fraud Analytics and Tools
The Many Faces of Fraud Analytics
The Paper Chase Is Over
To Be or Not to Be
Visual Links Analytics
FICO Insurance Manager 3.3
IBM® i2® iBase
Palantir Tech
Fiserv’s AML Manager
Notes
About the Author
Index
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