There is a new version of this course. Please see Using SAS Risk Modeling.

SAS Risk Modeling enables you to quickly and efficiently create analytical base tables that are used for developing credit scoring models. In this course, you learn how to create analytical base tables by calculating variables from different sources. Using Model Studio to develop an application scorecard is demonstrated and practiced. By the end of this course, you will be comfortable working in Risk Modeling workspaces that are used for implementing models and monitoring their performance.

Learn how to

• Explain the business purpose and use of SAS Risk Modeling.
• Create an analytical base table (ABT).
• Generate a scorecard model.
• Import models from a source model directory.
• Backtest a model.
• Deploy a model.
• Create reports on credit scoring models.

Who should attend

Credit/risk/business analysts in financial institutions who are responsible for building analytical base tables used for modeling, as well as model specification, deployment, backtesting, and monitoring

Formats available	Standard duration
Classroom:	2 days

This course is for modelers and analysts who have a basic understanding of the credit scoring process. Introductory knowledge of SAS tools such as Model Studio is helpful but not required.

This course addresses SAS Risk Modeling software.

Risk Modeling Solution Overview

• Solution overview.
• SAS Viya overview.

Analytical Data Builder

• Data Preparation Workspace overview.
• Create project.
• Data set parameters.
• Target population.
• Variables.
• Build data set.

Data Configuration Workspaces

• Data Configuration Workspaces overview.

Risk Modeling Add-on for SAS Visual Machine Learning

• SAS Visual Data Mining and Machine Learning overview.
• Interactive Grouping node.
• Scorecard node.
• Reject Inference node.

Risk Modeling

• Model specification.
• Backtesting.

Additional Topics

• Caslibs.
• SAS content.
• Report.