Conceptual and Statistical Issues Regarding the Probability of Default and Modeling Default Risk

Abstract

In today’s rapidly evolving financial markets, risk management offers different techniques in order to implement an efficient system against market risk. Probability of default (PD) is an essential part of business intelligence and customer relation management systems in the financial institutions. Recent studies indicates that underestimating this important component, and also the loss given default (LGD), might threaten the stability and smooth running of the financial markets. From the perspective of risk management, the result of predictive accuracy of the estimated probability of default is more valuable than the standard binary classification: credible or non credible clients. The Basle II Accord recognizes the methods of reducing credit risk and also PD and LGD as important components of advanced Internal Rating Based (IRB) approach.

Keywords

• probability of default
• stress test
• PD buckets
• pooled PDs
• predictive analytics
• data mining techniques
• statistical methods
• loss given default