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.
- recognize the different uses for credit risk scorecards
- recognize the main personas involved in successful credit scoring projects
- plan a successful scorecard development project
- develop grouped-variable, points-based credit risk scorecards, from start to finish
- perform validation, use multiple scorecards, set cutoffs
- develop strategies using scorecards
- create reports on scorecard validation and maintenance.
Who Can Benefit
- Credit risk/scoring managers and data miners; those involved in model vetting/validation and auditing; risk strategy developers; and credit risk executives
- No SAS experience or programming experience is required. Students should be familiar with logistic regression. Knowledge of SAS Enterprise Miner is helpful, but not necessary. Business experience is preferred, particularly in the following sectors: