ISW Secure Payments Training
better customise ISW SECURE Payments to your organisation's needs
Unlock the full potential of your ISW Secure Payments service and take your organisation to new heights with these comprehensive training courses. Not only will you gain an in-depth knowledge into the rules and models that apply, but also valuable skills for customising them to meet specific needs - boosting efficiency, productivity and reducing fraud.
ISW Secure Payments
Modeler Course
Description: This course empowers students to create rules using a variety of profiling tools to address a variety of fraud schemes. There is particular focus on the simulation and AI capability within ISW Secure Payments service to ensure accuracy of models & rules which greatly extends your counter fraud capability.
Prerequisites: None | Duration: 3 Days
Course Outline
Day 1 – Profiling
Introduction
Messages, Attributes & Indexes
Conditions & Expressions
Approaches to Fraud Rules
Profiling Behaviour
Writing Rules
Day 2 – Writing Rules
Compliance List
White, Black and Grey Lists
Practical Fraud Rules
Practical AML Rules
Collusions (Point of Compromise)
Day 3
Sampling
Simulations
Rule Generation
Internal Random Forest Model
Upon Completion the student will be able to:
Write rules using a different profiling tools
Understand the different condition expressions
Profile normal vs abnormal behaviour
Configure Compliance Lists
Configure Risk Lists
Configure a Collusion
Run Simulations
Generated rules and understand parameter settings
Generated a Random Forest Model and understand parameter settings
ISW Secure Payments
Advanced Modeler Course
Description: This course builds on the Modeler course stepping through using python to leverage external models; and then making use of modelling tools to create models that are imported into the ISW Secure Payments service. These two approaches help identify patterns of fraud that were not obvious to the fraud team and will increase your hit rate while reducing your false positive rate.
Prerequisites: Completed the ISW Secure Payments modelling course. Some knowledge of Python
Duration: 2 Days
Course Outline
Day 1 –ISW SeCURER Payments with Python
Exporting Data
Introduction to Neural Networks & XGBoost AL models
Creating a Neural Network model using Python Tensorflow Library
Creating a XGBoost model using Python Tensorflow Library
Configuring Safer Payments to use Python
Accessing Neural Network model from Rules
Accessing XGBoost model from Rules
Day 2 – External Modelling
Creating an external model with modelling tools
Importing an external model
Creating an Ensemble Model
Accessing models as web services
Running a simulation using the external model
Upon Completion the student will be able to:
Explain the different AI models
Use python to access models
Create external models using modelling tools
Import external models
Access external models as web services using python
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