IBM Safer Payments: Hands-on Modeling Training Primer

IBM Safer Payments: Hands-on Modeling Training Primer (v6.4.x)

IBM Training for IBM Safer Payments: Hands-on Modeling Training Primer (v6.4.x)

Skill Level: Intermediate

Modality: CR – Classroom based Trainng or ILO – Instructor Led Online Class

Duration: 3 Day/s

Starting Price: $ – 1,807

Overview:

In this course, all of the IBM Safer Payments model capabilities are presented in detail.

IBM Safer Payments is an innovative real-time payment fraud prevention and detection solution for all cashless payment types. IBM Safer Payments provides not only model capabilities based on inbuilt tools, but also the option to import externally built fraud models for real-time decisioning. In this course, all of the IBM Safer Payments model capabilities are presented in detail. The following modelling concepts are covered: index, profiling techniques (with and without index sequence), model components comprised of rulesets, PMML, Python and Internal Random Forest, elements of the simulation environment including Rule Generation and Internal Random Forest, as well as the sampling techniques. All these concepts will be followed by the hands-on exercises.

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Target Audience:

External: Fraud Analysts, Application and System Admins managing Safer Payments (optional), Internal: IBM Lab Services, IBM Support, IBM Technical Pre-Sales and IBM Business Partners.

Prerequisites: Must be familiar with Unix command line navigation and configuration actions

Some familiarity with statistical models
Knowledge in Fraud Prevention for cashless payments

Topic: Day 1: 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:Introduction to Simulation workflow

Sampling Techniques
Rule Analyses and Rule Performance
Rule Performance and Rule Scoring

Day 3:Internal modeling capabilities (Rule Generator and Random Forest)

Exporting and importing data for external modeling
Python callouts
PMML Model Import
Point of Compromise

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Objective: The objective of this course is to teach students the following topics:

Mandator structure
Modeling concepts
Profiling concept
Rulesets and Rules
Simulation environment
Analysis
Model components
Python callouts

Category: Industry

Product Name:

IBM Safer Payments

Badge and Certification Info:

Badge Title: IBM Safer Payments: Hands-on Modeling Training Primer (v6.4.x) – Code: 6A430G

Badge ID: 71ee974d-dc19-4a33-be9c-0fa040d808e4

Brand: WFSS – Financial Crimes and Conduct Risk

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