IBM Safer Payments Modeling Training (V6.6)

Day 1: Modeling approaches and Profiling

• Safer Payments Data Dictionary
• Modeling Approach (Internal & External Modeling)
• Examine Indexes with and without sequences
• Profiling in Safer Payments using index with sequence (Counter, Precedents, Pattern) 
• Profiling in Safer Payments using index without sequence (Calendar, Events, Device Identification, Formulas) 
• Introduction to Rules 

Day 2: Rules and Simulation

• Introduction to Simulation workflow
• Sampling Techniques
• Rule Analyses and Rule Performance
• Rule Performance and Rule Scoring

Day 3: Model Factory and External Models

• Internal modeling capabilities (Rule Generator and Random Forest)
• Exporting and importing data for external modeling 
• Python callouts
• PMML Model Import
• Point of Compromise

• External: Fraud Analysts, Application and System Administrators who manage Safer Payments (optional)
• Internal: IBM Lab Services, IBM Support, IBM Technical Pre-Sales and IBM Business Partners

• Must be familiar with Unix command line navigation and configuration actions
• Some familiarity with statistical models
• Knowledge in Fraud Prevention for cashless payments

• Mandator structure 
• Modeling Concepts 
• Profiling Concept
• Rulesets and Rules
• Simulation Environment 
• Analysis
• Model Components
• Python callouts