In this hands-on course, risk modelers learn how to manage models and related risk objects. Updates to SAS code models and modeling systems used in the monthly production cycle are demonstrated and practiced. Related model risk objects such as risk scenarios and attribution templates are introduced and modified. Students will become comfortable working in SAS Risk Stratum work spaces that are used for updates and changes to statistical models.
The self-study e-learning includes:
- Annotatable course notes in PDF format.
- Virtual lab time to practice.
Learn how to
- Create new model objects and register them for use in SAS Risk Stratum.
- Work with sample credit risk models.
- Update modeling systems in SAS Model Implementation Platform.
- Work with SAS code and other code models, including Python, R, and Lua.
- Create and use model parameters to provide additional processing instructions.
- Add pre- and post-run processing to a credit risk model run.
- Submit and analyze model run results.
- Prepare master risk scenarios and include them in a credit risk model analysis run.
- Create and modify attribution templates and then run an attribution analysis and interpret results.
Who should attend
Risk modelers who are responsible for modeling activities that calculate expected credit loss using SAS Risk Stratum
This course is for experienced modelers and analysts who have expertise using statistical modeling concepts and methods. Experience with SAS programming language is helpful but not required.
This course addresses SAS Expected Credit Loss software.
