1st Edition
Data Mining for Intelligence, Fraud & Criminal Detection Advanced Analytics & Information Sharing Technologies
Overview
Introduction
Sharing Data
Connect the Dots
Analytical Versus Referential Data
Information Sharing
Conclusion
The Quality of Data
Introduction
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
What Are Patterns?
Introduction
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
Border Protection
Introduction
I-94 Arrival/Departure Records
Land Border Targeting
Cluster by Hour of the Day (HOD)
Cluster by Day of the Week (DOW)
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
Money Laundering and Financial Crimes
Introduction
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
False Temporal Patterns
A Final Note
Conclusion
Money Service Businesses
Introduction
What Is a Money Service Business?
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
Elder Abuse Pattern
Ornery Old Man
Other MSB Patterns
Multiple Locations
Minimal Overlaps
Official Deposits
Heavenly Offerings
Dirty Dancing
Conclusion
Fraud Analytics
Introduction
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
Medicare Claim Fraud
Conclusion
Information-Sharing Protocols
Introduction
Global Justice XML Data Model (Global JXDM)
Data Dictionary
Data Model
Component Reuse Repository
National Information Exchange Model
28 CFR Part 23
Conclusion
Information-Sharing Systems
Introduction
Automated Regional Justice Information System (ARJIS)
Citizen and Law Enforcement Analysis and Reporting (CLEAR)
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 Area (HIFCA)
Regional Information Sharing System (RISSs)
Conclusion
Summary
Biography
Christopher Westphal
"…this book should be mandatory reading for every Crime Analyst. I’ve seen a lot of this info before but never in one place before nor with the level of explanation and examples."
—Michael P. Ley, Antiterrorism Officer (ATO) & Intelligence Coordinator, U.S. Marine Corps Support Facility-Blount Island, Jacksonville, FL, USA
