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Practical Fraud Prevention
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Practical Fraud Prevention
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Practical Fraud Prevention
1. Fraudster Archetypes
Amateur Fraudsters
Mechanical Turk Fraudsters
Psychological Fraudster
Product-savvy Fraudster
Tech-Savvy Fraudster
Bot Generator
Hacker
Organized Fraud Crime
Distinction Between Organized Crime and Mechanical Turk Fraudsters
Small But Organized Crime
Friendly Fraudsters
Pop Quiz
Summary
2. Fraud Analysis Fundamentals
Thinking Like A Fraudster
A Professional Approach to Fraud
Treat Categories with Caution
Account Versus Transaction
Between Blocking Fraud and Avoiding Friction: A Balance
Anomaly Detection
Practical Anomaly Detection - Density Case Study
Crises: Planning and Response
Economic Stress Affects Consumers’ Situations - and Decisions
Prepare for Shifts in User Behaviors
Inter-Departmental Communication and Collaboration
Friendly Fraud
Summary
3. Fraud Prevention Evaluation and Investment
Types of Fraud Prevention Solutions
Rules Engines
Machine Learning
Hybrid Systems
Data Enrichment Tools
Consortium Model
Building A Res earch Analytics Team
Collaborating With Customer Support
Measuring Loss and Impact
Justifying the Cost of Fraud Prevention Investment
Inter-Departmental Relations
Data Analysis Strategy
Fraud Tech Strategy
Data Privacy Considerations
Identifying and Combating New Threats Without Undue Friction
Keeping Up With New Fraud Fighting Tools
Summary
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