This course is part one of a two course series. It concentrates on rating system use and maintenance aspects, including validation and re-calibration, while the second course concentrates on the creation of rating models.
The topics in this first course relate more to the Business-As-Usual activities of a credit risk management team, while model creation often takes the form of projects, which may sometimes be outsourced to third parties. Having said that, it is strongly advised for everybody working in this field to have a good understanding of all rating system aspects.
This course starts with an overview of the components of individual risk prediction and explains the risk parameters PD, LGD and EAD. After that, various uses of risk predictions are explained. Special attention is given to credit approval topics and risk weighted asset calculation. To end the introductory part, an overview of the tasks involved in maintaining prediction quality is given.
The focus then shifts to the organisation of the historical data that is at the center of all risk prediction. Various functional distinctions that the data mart must account for are laid out and a general structure of the modelling and validation tables that form the end product of the data integration efforts is given. It is in this part that we cover the central definition of the default indicator. Also the various types of characteristics that are typically available to describe a case are discussed here.
On the basis of a risk prediction data mart the quality of rating models can then be assessed. We cover a variety of widely used measures of key model quality aspects, such as calibratedness, discriminatory power and stability and discuss their interrelatedness and their interpretation in the light of economic cycles. Regulatory requirements and qualitative aspects of rating system validation are covered as well.
Finally, models may be re-calibrated without performing a full model re-build. We discuss mathematical re-calibration techniques as well as the rationale behind re-calibration.