Overview:
This one-day course is intended to equip participants with the skills they need to design, develop, and implement credit scoring models to facilitate sound consumer lending decisions, and to achieve improvements in acceptance rates and reductions in bad debt.
Duration: 8 hours
Who should attend?
Credit risk executives, risk managers, risk analyst, risk strategy developers, credit managers, predictive analysts from financial, insurance, retail or telecom organizations.
Learn how to:
- Understand the pros and cons of developing statistically-based, judgmental and credit bureau scoring
- Understand Statistical Credit scorecard development stages
- Develop and validate intelligent credit risk scorecards
- Prepare credit portfolio data for the statistical scorecard development process
- Analyze data quality and select customer attributes with IV, correlation and WOE
- Build statistical scorecards using logistic regression
- Generate and analyze scorecard performance graphs and reports
- Assess scorecard quality with K-S, Gini, ROC and Lorentz curves
- Analyze score distributions and other scorecard validation graphs
- Apply best practices for setting appropriate scorecard cut-offs and associated business policies
- Use scorecards for loan origination
- Apply a Champion-Challenger approach for constant scoring quality improvement
- Monitor credit scorecard performance using front-end and back-end reports, PSI and Chi-square approach
All our scoring trainings.