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| Title | Credit Risk Analytics: Measurement Techniques, Applications, and Examples in SAS |
| Author | Bart Baesens, Daniel Roesch, Harald Scheule, & 0 More |
| ISBN-13 | 9788126567027 |
| Publication | WILEY |
Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management. Combining theory with practice, this book walks you through the fundamentals of credit risk management and shows you how to implement these concepts using the SAS credit risk management program, with helpful code provided. Coverage includes data analysis and preprocessing, credit scoring; PD and LGD estimation and forecasting, low default portfolios, correlation modeling and estimation, validation, implementation of prudential regulation, stress testing of existing modeling concepts, and more, to provide a one-stop tutorial and reference for credit risk analytics.
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Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management. Combining theory with practice, this book walks you through the fundamentals of credit risk management and shows you how to implement these concepts using the SAS credit risk management program, with helpful code provided. Coverage includes data analysis and preprocessing, credit scoring; PD and LGD estimation and forecasting, low default portfolios, correlation modeling and estimation, validation, implementation of prudential regulation, stress testing of existing modeling concepts, and more, to provide a one-stop tutorial and reference for credit risk analytics.
Bart Baesens, Daniel Roesch, Harald Scheule, & 0 More is the author of Credit Risk Analytics: Measurement Techniques, Applications, and Examples in SAS.
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| Title | Credit Risk Analytics: Measurement Techniques, Applications, and Examples in SAS |
| Author | Bart Baesens, Daniel Roesch, Harald Scheule, & 0 More |
| ISBN-13 | 9788126567027 |
| Publication | WILEY |
Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management. Combining theory with practice, this book walks you through the fundamentals of credit risk management and shows you how to implement these concepts using the SAS credit risk management program, with helpful code provided. Coverage includes data analysis and preprocessing, credit scoring; PD and LGD estimation and forecasting, low default portfolios, correlation modeling and estimation, validation, implementation of prudential regulation, stress testing of existing modeling concepts, and more, to provide a one-stop tutorial and reference for credit risk analytics.