Credit Scorecard Development and Implementation

Course code: CSDI7

This 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.

1 200 EUR

1 452 EUR including VAT

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Course dates

Starting date: Upon request

Type: Upon request

Course duration: 14 hours

Language: en

Price without VAT: 1 200 EUR

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Target group

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

Course structure

Introduction to Credit Risk

  • risk management areas
  • terminology
  • applications of credit scoring in various industries

Preliminaries and Planning

  • create business plan: identify organizational objectives; and internal vs. external development, and scorecard type
  • create project plan: identify project risks and Identify project team

Data Review and Project Parameters

  • data availability and quality review
  • data gathering for definition of project parameters
  • definition of project parameters: performance window and sample window, performance categories definition, and exclusions
  • segmentation

Development Database Creation

  • development sample specifications
  • development data collection and construction
  • adjusting for prior probabilities/factoring

Model Development

  • missing values and outliers
  • initial characteristic analysis (binning): statistical measures and logical trend
  • building a preliminary scorecard using logistic regression
  • reject inference
  • final scorecard production: scaling, misclassification, and scorecard strength measures
  • validation

Scorecard Management Reports

  • gains tables
  • characteristic reports

Pre-Implementation

  • pre-implementation validation: scoring accuracy and front end validation

Strategy Development

  • strategy development considerations
  • scoring strategies
  • setting cutoffs
  • strategy actions
  • policy rules
  • overrides

Post-Implementation

  • review/postmortem
  • reporting: system stability, characteristic, override, final score, delinquency, and vintage

Prerequisites

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/finance
  • retail
  • insurance
  • telecommunications.
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