This book provides a systematic presentation of credit risk scorecard development and implementation. The text covers the theoretical foundations, the practical implementation and programming using SAS. The book topics include: - Data acquisition - data preparation - EDA, predictive measures and variable selection - Optimal segmentation and binning - Coarse classing and WOE transformations - Development of logistic regression models - Methods of model assessment and evaluation - Scorecard creation and scaling - Automatic generation of scoring code (SAS, SQL, C) - Scorecard monitoring and reporting - Reject inference The SAS implementation contains over 50 ready-to-use SAS macros that can be implemented in the automation of the scorecard creation process.
This book provides a systematic presentation of credit risk scorecard development and implementation. The text covers the theoretical foundations, the practical implementation and programming using SAS. The book topics include: - Data acquisition - data preparation - EDA, predictive measures and variable selection - Optimal segmentation and binning - Coarse classing and WOE transformations - Development of logistic regression models - Methods of model assessment and evaluation - Scorecard creation and scaling - Automatic generation of scoring code (SAS, SQL, C) - Scorecard monitoring and reporting - Reject inference The SAS implementation contains over 50 ready-to-use SAS macros that can be implemented in the automation of the scorecard creation process.