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Validating Consumer Credit Risk Models: What Methods Are Relevant to Assuring Your Model's Stability in a Volatile Business EnvironmentPublished by: IDC Published: Apr. 14, 2009 - 18 Pages Table of ContentsTable of Contents Financial Insights Opinion In This Report Situation Overview Variability Within a Population Consumer Behavior Who Uses Validations? Who Should Perform Validation Analytics? How Validations Fit Within an Enterprise Risk Management Context Method Specifics Tracking Through-the-Door Populations Final Score Report Figure: Final Score Report Population Stability Figure: Population Stability Characteristic Analysis Figure: Characteristic Level Changes Interval Bad Rates Figure: Interval Bad Rate Analysis Validation Sample Components of a Score Validation Statistical Measures Used in Score Validations Kolmogorov-Smirnov Statistic Figure: Kolmogorov-Smirnov Statistic Divergence Figure: Divergence Predictiveness Index Figure: Predictiveness Index Information Value Figure: Information Value Future Outlook Essential Guidance Actions to Consider Learn More Related Research Synopsis AbstractThis Financial Insights report details why a validation is essential, the appropriate steps to carry out a validation analysis, and who the business constituents are that rely on validations and also details what we mean by model "performance." "As the global economy struggles in recession, lenders across industry verticals should closely track and validate their scoring models. During economic times of rapid expansion and contraction, scoring models can degrade in their ability to make optimal loan recommendations. Sound population and scorecard tracking and validation practices are part of a robust enterprise risk management program." - Dana Wiklund, research director, Global Risk Management Get Full Details About This Report >> |
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