Credit risk modelling and valuation: testing credit rating accuracy in default prediction.

Abstract

Credit risk is a forward-looking concept, focusing on the probability of facing credit difficulties in the future. Credit difficulties are represented by the risk of not being paid for goods or services sold to customers. This kind of risk involves all companies from financial services industry to consumer goods. Credit risk has acquired growing importance in recent years which have been characterized by a negative economic situation, started with the US subprime mortgage crisis and the collapse of Lehman Brothers in 2008. The financial crisis intervened before Basel II could become fully effective, and unveiled the fragilities of the financial system in general, but also emphasised the inadequacy of both credit risk management and the connected credit rating system carried out by ECAIs. In Chapter I, starting from an historical excursus, the study deals with credit risk methods and rating capability to predict firms’ probability of default, taking into account both quantitative and qualitative methods and the consequent credit rating assessment. In Chapter II we focus on the trade credit insurance case. Credit insurance allows companies of any size to protect against the risk of not being paid, and this consequently increases firm’s profitability thanks to higher client portfolio quality. This means that the analysis of creditworthiness includes a wide population, from SMEs to large corporates. In Chapter III we provide an empirical analysis on the accuracy of rating system: we start from dealing with the distribution of the Probability of Default and firms’ allocation in PD classes, we analyse the Gini coefficient’s adequacy in measuring rating accuracy and we deal with a multiple regression model based on financial indicators. Finally we conclude with reflections and final comments.