Credit Risk Analytics

Regular price €81.99
Quantity:
In stock with our UK publisher. 14-28 days
Delivery/Collection within 10-20 working days
14 days return policy Shipping & Delivery
A01=Bart Baesens
A01=Daniel Roesch
A01=Harald Scheule
and Examples in SAS
Applications
Author_Bart Baesens
Author_Daniel Roesch
Author_Harald Scheule
Bart Baesens
Bayesian statistics
Category=KFFL
Category=PBWH
corporate credit analysis
correlations
Credit Risk Analytics: Measurement Techniques
credit risk concepts
credit risk management
credit risk model testing
credit risk model validation
Daniel Roesch
default risk
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
exposure at default
financial modeling
Harald Scheule
how to model credit risk
LGD
loss distributions
loss given default
low default portfolios
measuring credit risk in SAS
modeling capital management
modeling credit risk
PD
point-in-time
practical credit risk modeling
probabilities of default
risk management modeling
risk modeling guide
SAS credit analysis
SAS modeling
scoring
through-the-cycle

Product details

  • ISBN 9781119143987
  • Weight: 1179g
  • Dimensions: 185 x 239mm
  • Publication Date: 25 Nov 2016
  • Publisher: John Wiley & Sons Inc
  • Publication City/Country: US
  • Product Form: Hardback
Secure checkout Fast Shipping Easy returns
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.

BART BAESENS is a professor at KU Leuven (Belgium) and a lecturer at the University of Southampton (United Kingdom).

DANIEL RÖSCH is a professor in business and management and chair in statistics and risk management at the University of Regensburg (Germany).

HARALD SCHEULE is an associate professor of finance at the University of Technology Sydney (Australia) and a regional director of the Global Association of Risk Professionals.

More from this author