The probability of default (PD) of a borrower or group of borrowers is the central measurable concept on which the IRB approach is built.
The probability of default of a borrower does not, however, provide the complete picture of the potential credit loss. Banks also seek to measure how much they will lose should a borrower default on an obligation.
Although, time consuming, calculating the PDs can be automated. Probability analysis risk modelling software such as SAS, CrossWalk and Algorithmics makes the process much easier and indeeds helps guide the user through this difficult process. Indeed the websites of such Risk Software companies, incl Algorithmics, Standard and Poors and SAS, contains many useful white papers that help describe the process of calculating PD values.
The PD is contingent upon two elements. First, the magnitude of likely loss on the exposure: this is termed the Loss Given Default (LGD), and is expressed as a percentage of the exposure. Secondly, the loss is contingent upon the amount to which the bank was exposed to the borrower at the time of default, commonly expressed as Exposure at Default (EAD).
These three components ( probability of default, LGD, EAD) combine to provide a measure of expected intrinsic, or economic, loss.
All banks, whether using the foundation or advanced methodologies, must provide supervisors with an internal estimate of the probability of default associated with borrowers in each borrower grade. Each estimate of probability of default must represent a conservative view of a long-run average PD for the grade in question, and thus must be grounded in historical experience and empirical evidence. Preparation of the estimates, and the risk management processes and rating assignments that lay behind them, must reflect full compliance with supervisory minimum requirements (including internal use and disclosure requirements associated with the estimates) to qualify for IRB recognition.