Go to content
UR Home

Credit Risk Analytics: The R Companion

Scheule, Harald ; Rösch, Daniel ; Baesens, Bart



Abstract

Credit risk analytics in R will enable you to build credit risk models from start to finish. Accessing real credit data via the accompanying website www.creditriskanalytics.net, you will master a wide range of applications, including building your own PD, LGD and EAD models as well as mastering industry challenges such as reject inference, low default portfolio risk modeling, model validation and ...

plus


Owner only: item control page
  1. Homepage UR

University Library

Publication Server

Contact:

Publishing: oa@ur.de

Dissertations: dissertationen@ur.de

Research data: daten@ur.de

Contact persons