There is a new version of this course. Please see Credit Scorecard Development and Implementation.

Presented by Naeem Siddiqi, Senior Advisor, SAS Risk Research and Quantitative Solutions and author of Intelligent Credit Scoring: Building and Implementing Credit Risk ScorecardsThis business-focused course provides a high-level introduction to credit risk management; detailed end-to-end methodology training for risk scorecard development for retail and SME portfolios; and discussions on scorecard implementation and risk strategy development, and scorecard and portfolio management reporting. The focus of the course is the development of application scorecards, but issues relating to behavior scorecard development will also be explored. Issues relevant to Basel II will be covered. These objectives are reflected in three sections.Section 1, Introduction to Credit Risk: Students will get a high-level overview of the credit risk industry, risk management tools, and strategies. Students will understand the different uses of credit risk scorecards and learn industry terminology, as well as understand the main personas involved in successful credit scoring projects.Section 2, Risk Scorecard Development: Students will learn how grouped-variable, points-based credit risk scorecards are developed, from the planning stages to delivery. While the main focus will be on business issues, statistical aspects of scorecard development will also be explored.Section 3, Implementation and Maintenance: This section will cover post-development activities including setting cutoffs, strategy development, and scorecard maintenance reports.

Learn how to

recognize the different uses for credit risk scorecardsrecognize the main personas involved in successful credit scoring projectsplan a successful scorecard development projectdevelop grouped-variable, points-based credit risk scorecards, from start to finishperform validation, use multiple scorecards, set cutoffsdevelop strategies using scorecardscreate reports on scorecard validation and maintenance.

Who should attend

Credit risk/scoring managers and data miners; those involved in model vetting/validation and auditing; risk strategy developers; and credit risk executives

Formats available	Duration
Live Web Classroom:	5 x 5-hour sessions

No SAS experience or programming experience is required. Students should be familiar with logistic regression. Knowledge of SAS Enterprise Miner is helpful, but not necessary. Business experience is preferred, particularly in the following sectors:

banking/financeretailinsurancetelecommunications.

This course addresses SAS Risk Management software. Although the solution is used to illustrate the examples, the course is software-neutral. There are no hands-on programming exercises in this course.

This course addresses SAS Risk Management software.

Introduction to Credit Riskrisk management areasterminologyapplications of credit scoring in various industriesPreliminaries and Planningcreate business plan: identify organizational objectives; and internal vs. external development, and scorecard typecreate project plan: identify project risks and Identify project teamData Review and Project Parametersdata availability and quality reviewdata gathering for definition of project parametersdefinition of project parameters: performance window and sample window, performance categories definition, and exclusionssegmentationDevelopment Database Creationdevelopment sample specificationsdevelopment data collection and constructionadjusting for prior probabilities/factoringModel Developmentmissing values and outliersinitial characteristic analysis (binning): statistical measures and logical trendbuilding a preliminary scorecard using logistic regressionreject inferencefinal scorecard production: scaling, misclassification, and scorecard strength measuresvalidationScorecard Management Reportsgains tablescharacteristic reportsPre-Implementationpre-implementation validation: scoring accuracy and front end validationStrategy Developmentstrategy development considerationsscoring strategiessetting cutoffsstrategy actionspolicy rulesoverridesPost-Implementationreview/postmortemreporting: system stability, characteristic, override, final score, delinquency, and vintage