Advanced Credit Risk Modeling for Basel II Using SAS
Course Description
Prerequisites
The course assumes that the participants have the following background knowledge:
- basic implications of the Basel II Capital Accord
- difference between Application Scoring/Behavioural Scoring/Profit Scoring
- preprocessing for credit scoring (weights of evidence, outliers, missing values, coarse classification)
- know how to develop scorecards using logistic regression
- setting cut-offs; dealing with reject inference
- measuring scorecard performance.
We note that these topics are covered in the Basic Credit Risk Modeling for Basel II Using SAS course.
Course Contents
A Review of Basel II and PD Modeling
- Basel I and Basel II
- a brief review of PD modeling
- portfolio models for credit risk: the Merton model
- Basel II capital requirement formulas
Modelling LGD and EAD
- modelling Loss Given Default (LGD)
- defining LGD (workout approach, market approach, etc.)
- creating an LGD data set
- estimating LGD models
- defining LGD ratings and calibration
- modelling Exposure at Default (EAD)
- correlations between PD, LGD, and EAD
Validating and Stress Testing PD, LGD, and EAD Models
- validating PD, LGD, and EAD models
- quantitative versus qualitative validation
- quantitative validation
- qualitative validation
- Traffic Light Indicator approach
- backtesting PD models
- backtesting LGD and EAD models
- benchmarking
- stress testing for PD, LGD, and EAD
- Low Default Portfolios (LDPs): implementation and validation
New Techniques to Develop PD, LGD, and EAD Models for Basel II
- a brief review of traditional techniques for scorecard development
- neural networks
- Support Vector Machines
- survival analysis
Software Addressed
This course addresses the following software product(s): SAS Enterprise Miner, SAS for Enterprise Risk Management.
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