Training Formats:= Classroom
= Live Web Classroom
Credit Scorecard Development and Implementation
This business-focused course provides a high-level introduction to credit risk management; detailed end-to-end methodology training for risk scorecard development for retail and SME portfolios; and discussions on scorecard implementation and risk strategy development, and scorecard and portfolio management reporting. The focus of the course is the development of application scorecards, but issues relating to behavior scorecard development will also be explored. Issues relevant to Basel II will be covered. These objectives are reflected in three sections.
Section 1, Introduction to Credit Risk: Students will get a high-level overview of the credit risk industry, risk management tools, and strategies. Students will understand the different uses of credit risk scorecards and learn industry terminology, as well as understand the main personas involved in successful credit scoring projects.
Section 2, Risk Scorecard Development: Students will learn how grouped-variable, points-based credit risk scorecards are developed, from the planning stages to delivery. While the main focus will be on business issues, statistical aspects of scorecard development will also be explored.
Section 3, Implementation and Maintenance: This section will cover post-development activities including setting cutoffs, strategy development, and scorecard maintenance reports.
Credit Risk Modeling
In this course, students learn how to develop credit risk models in the context of the Basel guidelines. The course provides a sound mix of both theoretical and technical insights, as well as practical implementation details. These are illustrated by several real-life case studies and exercises.
Applied Analytics Using SAS Enterprise Miner
This course is appropriate for SAS Enterprise Miner from release 5.3 up to 14.2. The course covers the skills that are required to assemble analysis flow diagrams using the rich tool set of SAS Enterprise Miner for both pattern discovery (segmentation, association, and sequence analyses) and predictive modeling (decision tree, regression, and neural network models).