Basel II reports in
SAS Model Manager provide several statistical measures and tests to
validate stability, performance, and calibration using Loss Given
Default (LGD) and Probability of Default (PD) models.
Model stability measures
The model stability
measures track the change in distribution of the modeling data and
the scoring data.
Model performance measures
The model performance
measures report this information:
-
The model’s ability to discriminate
between accounts that have defaulted and those that have not defaulted.
The score difference between the accounts that default and those that
do not helps determine the cut-off score, which is used to predict
whether a credit exposure is a default.
-
The relationship between the actual
default probability and the predicted probability. This information
is used to understand a model’s performance over a period of
time.
Model calibration measures
The model calibration
measures check the accuracy of the LGD and PD models by comparing
the correct quantification of the risk components with the available
standards.
For a description
of the statistical measures, see Statistical Measures Used in Basel II Reports in SAS Model Manager: User's Guide.The tutorial provides
examples and step-by-step directions for importing LGD and PD models
and creating Basel II reports.