Developing an Application Scorecard using SAS

Learn the entire process of application scorecard development using SAS. Understand key concepts like Reject inference.

Ratings: 5.00 / 5.00




Description

The "Developing an Application Scorecard using SAS" course is designed to equip participants with the knowledge and practical skills necessary to build robust application scorecards using SAS software. Application scorecards are critical tools used by financial institutions to assess the creditworthiness of new applicants and make well-informed lending decisions. This course will guide participants through the entire process of developing an application scorecard, from data preparation and variable selection to model development, validation, and deployment.

Course Objectives:

By the end of this course, participants will:

  1. Understand the fundamentals of credit risk assessment and the significance of application scorecards in the lending process.

  2. Learn how to use SAS software for data manipulation, data preparation, and statistical analysis in the context of credit risk modeling.

  3. Develop expertise in data preprocessing techniques, including data cleaning, imputation, and outlier handling.

  4. Master the process of feature engineering to create informative variables for the application scorecard.

  5. Gain practical experience in building and optimizing predictive models using SAS for credit risk evaluation.

  6. Implement model validation techniques to ensure the accuracy and reliability of the application scorecard.

  7. Understand the best practices for scorecard implementation, monitoring, and ongoing maintenance.

Target Audience: This course is ideal for credit risk analysts, risk managers, data analysts, and professionals working in financial institutions who want to enhance their skills in application scorecard development using SAS. It is also suitable for individuals interested in credit risk modeling and decision-making in the lending industry.

What You Will Learn!

  • Introduction to Credit Risk and Application Scorecards
  • SAS Fundamentals for Credit Risk Modeling
  • Data Preprocessing for Application Scorecard
  • Feature Engineering for Application Scorecards
  • Building Predictive Models with SAS
  • Model Validation
  • Reject Inference in SAS Enterprise Miner

Who Should Attend!

  • Credit Risk Analysts and Credit Risk Managers
  • Data Analysts and Data Scientists
  • Risk Managers and Risk Analysts
  • Students and Academicians
  • Professionals Transitioning into Credit Risk