This course teaches students how to build a credit scorecard from start to finish using SAS Enterprise Miner 14.2 and the methodology recommended by leading credit and financial experts.
The self-study e-learning includes:
- Annotatable course notes in PDF format.
- Virtual Lab time to practice.
Learn how to
- use the SAS Enterprise Miner Interactive Grouping node to select the predictive variables using Information Value and calculate Weight of Evidence values
- use the SAS Enterprise Miner Scorecard node to build a preliminary scorecard using the appropriate scaling methodology
- perform reject inference techniques such as hard cut-off augmentation, parceling, and fuzzy augmentation using the SAS Enterprise Miner Reject Inference node in order to augment the scorecard by using rejected applicants
- determine how well the scorecard performs using scorecard diagnostic tools such as ROC and Lift charts.
Who should attend
Risk analysts, credit modelers, credit scorecard developers, credit managers, credit analysts, and business analysts in banks and other financial institutions who are responsible for development of scorecards and credit-scoring applications
Before attending this course, students should have a working knowledge of the statistics of finance and scorecard development, as well as basic skills using SAS Enterprise Miner. Students can gain knowledge of scorecard development by completing the Credit Scorecard Development and Implementation course. For skills using SAS Enterprise Miner, students should complete the Applied Analytics Using SAS Enterprise Miner course or have equivalent skills.
This course addresses SAS Enterprise Miner, SAS Risk Management software.
