Credit Risk Analytics

Measurement Techniques, Applications, and Examples in SAS

Business & Finance, Finance & Investing, Banks & Banking, Finance
Cover of the book Credit Risk Analytics by Bart Baesens, Daniel Roesch, Harald Scheule, Wiley
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Bart Baesens, Daniel Roesch, Harald Scheule ISBN: 9781119278283
Publisher: Wiley Publication: September 19, 2016
Imprint: Wiley Language: English
Author: Bart Baesens, Daniel Roesch, Harald Scheule
ISBN: 9781119278283
Publisher: Wiley
Publication: September 19, 2016
Imprint: Wiley
Language: English

The long-awaited, comprehensive guide to practical credit risk modeling

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. The companion website offers examples of both real and simulated credit portfolio data to help you more easily implement the concepts discussed, and the expert author team provides practical insight on this real-world intersection of finance, statistics, and analytics.

SAS is the preferred software for credit risk modeling due to its functionality and ability to process large amounts of data. This book shows you how to exploit the capabilities of this high-powered package to create clean, accurate credit risk management models.

  • Understand the general concepts of credit risk management
  • Validate and stress-test existing models
  • Access working examples based on both real and simulated data
  • Learn useful code for implementing and validating models in SAS

Despite the high demand for in-house models, there is little comprehensive training available; practitioners are left to comb through piece-meal resources, executive training courses, and consultancies to cobble together the information they need. This book ends the search by providing a comprehensive, focused resource backed by expert guidance. Credit Risk Analytics is the reference every risk manager needs to streamline the modeling process.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

The long-awaited, comprehensive guide to practical credit risk modeling

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. The companion website offers examples of both real and simulated credit portfolio data to help you more easily implement the concepts discussed, and the expert author team provides practical insight on this real-world intersection of finance, statistics, and analytics.

SAS is the preferred software for credit risk modeling due to its functionality and ability to process large amounts of data. This book shows you how to exploit the capabilities of this high-powered package to create clean, accurate credit risk management models.

Despite the high demand for in-house models, there is little comprehensive training available; practitioners are left to comb through piece-meal resources, executive training courses, and consultancies to cobble together the information they need. This book ends the search by providing a comprehensive, focused resource backed by expert guidance. Credit Risk Analytics is the reference every risk manager needs to streamline the modeling process.

More books from Wiley

Cover of the book Simplified Robust Adaptive Detection and Beamforming for Wireless Communications by Bart Baesens, Daniel Roesch, Harald Scheule
Cover of the book Introduction to Sociological Theory by Bart Baesens, Daniel Roesch, Harald Scheule
Cover of the book Global Warming For Dummies by Bart Baesens, Daniel Roesch, Harald Scheule
Cover of the book Chemistry Workbook For Dummies by Bart Baesens, Daniel Roesch, Harald Scheule
Cover of the book Inflammatory Bowel Diseases by Bart Baesens, Daniel Roesch, Harald Scheule
Cover of the book Natural Products in Medicinal Chemistry by Bart Baesens, Daniel Roesch, Harald Scheule
Cover of the book The Zen of Fundraising by Bart Baesens, Daniel Roesch, Harald Scheule
Cover of the book The Care of Wounds by Bart Baesens, Daniel Roesch, Harald Scheule
Cover of the book Fish Pheromones and Related Cues by Bart Baesens, Daniel Roesch, Harald Scheule
Cover of the book A Short History of Migration by Bart Baesens, Daniel Roesch, Harald Scheule
Cover of the book Magnetic Nanomaterials by Bart Baesens, Daniel Roesch, Harald Scheule
Cover of the book Porous Media Transport Phenomena by Bart Baesens, Daniel Roesch, Harald Scheule
Cover of the book You Can Kill An Idea, But You Can't Kill An Opportunity by Bart Baesens, Daniel Roesch, Harald Scheule
Cover of the book Classical and Adaptive Clinical Trial Designs Using ExpDesign Studio by Bart Baesens, Daniel Roesch, Harald Scheule
Cover of the book Basic Option Volatility Strategies by Bart Baesens, Daniel Roesch, Harald Scheule
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy