Data mining for intelligence, fraud, & criminal detection : advanced analytics & information sharing technologies / Christopher Westphal.

CONTENTS

Chapter 1 - Overview
Sharing Data
Connect the Dots
Analytical Versus Referential Data
Information Sharing
Conclusion

Chapter 2 - The Quality of Data
Value Errors
Missing Data and Bad Structures
Unique Addresses
Distinct Phone Numbers
Individual ID Numbers
Anomalous Accounts
One of a Kind Transactions
Original Organizations
Perspicuous People
Entity Resolution
Anonymous Resolution
Conclusion

Chapter 3 - What are Patterns?
Which Pattern Is More Important?
Do These Patterns Make Sense?
Is This a Reliable Pattern?
Is This an Actionable Pattern?
Which Pattern is More Valuable?
What Does this Pattern Show?
Who is the Most Important Person?
Conclusion

Section 2 Introduction

Chapter 4 - Border Protection
I-94- Arrival/Departure Records
Land Border Targeting
Cluster by Hour of the Day (HOD)
Cluster by Day of the Week (DOW)
Figure 4.18. Date Grid Showing Crossing Behavior by Day/Week
Cluster by Date
Cluster by Port of Entry (POE)
Clusters by Lane
Cluster by Inspector
Cluster by City/State
Cluster by VIN
Putting It Together
Conclusion

Chapter 5 - Money Laundering and Financial Crimes
Suspicious Activity Reports
Structuring Transactions
Bust Out Schemes
A Consumer Bust-Out Scheme
Busting and Kiting
Identity Fraud
Large Connections
Attorneys and Law Firms
Cheap Motels
Location, Location, Location
Individual Taxpayer Identification Number
SAR Versus STR
Timing is Everything
A Final Note
Conclusion

Chapter 6 - Money Service Businesses
Why Wire Remitters?
Steps of a Wire Remittance
Structure of a Wire Transfer
Combating Human Smuggling
The Smuggling Process
Changing the Rules
Seizing Assets
Corridor States
Drug Dealers
Suspicious Activity Reports
Elderly Abuse Pattern
Ornery Old Man
Other MSB Patterns
Multiple Locations
Minimal Overlaps
Official Deposits
Heavenly Offerings
Dirty Dancing
Conclusion

Chapter 7 - Fraud Analytics
Warranty Fraud Anecdotes
Automobile Warranties
Hurricane Katrina
Corporate Frauds
Employees as Vendors
Vendors as Vendors
Corporate Expenses
Duplicate Payments
Human Resources
Gift Card Fraud
Additional Examples
Pharmaceutical
Phishing / Click Fraud
Tax Evasion
Conclusion

Section 3 Introduction

Chapter 8 - Information Sharing Protocols
Global Justice XML Data Model (Global JXDM)
Data Dictionary
Data Model
Component Reuse Repository
National Information Exchange Model
28 CFR Part
Conclusion

Chapter 9 - Information Sharing Systems
Automated Regional Justice Information System ARJIS
Comprehensive Regional Information Management Exchange System (CRIMES)
Factual Analysis Criminal Threat Solution (FACTS) System
Florida Information Network for Data Exchange and Retrieval (FINDER)
Ohio Local Law Enforcement Information Sharing Network (OLLEISN),
Law Enforcement Information Exchange (LInX)
OneDOJ , R-DEx, N-DEx
Law Enforcement Online (LEO)
Joint Regional Information Exchange System (JRIES)
Joint Terrorism Task Force (JTTF)
State-Level Fusion Centers
High Intensity Drug Trafficking Area (HIDTA)
High Intensity Financial Crime Areas (HIFCA)
Regional Information Sharing Systems (RISS)
Conclusion
Summary 1

Includes bibliographical references and index p. 411-426