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.

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 Formats available Duration
: 2 half day sessions

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 &csdi course. For skills using SAS Enterprise Miner, students should complete the course or have equivalent skills.

This course addresses SAS Enterprise Miner, SAS Risk Management software.

Scorecard Development Using SAS Enterprise Miner

• credit scoring background
• the scorecard development process using SAS Enterprise Miner

Accessing and Preparing Data for Scorecard Development

• creating a SAS Enterprise Miner project and diagram
• defining a data source
• creating development and validation data sets

SAS Enterprise Miner Interactive Grouping Node

• initial characteristic analysis
• interval variable binning options (self-study)
• special code options (self-study)
• grouping options (self-study)

Scorecard Node

• scorecard development
• adverse characteristics (self-study)

Reject Inference Node

• Reject Inference techniques using SAS Enterprise Miner
• Reject Inference Property Panel options (self-study)

CSEM42.