A semi-parametric Probability of Default model

Abstract: With the implementation of IFRS 9, a new set of impairment rules will be effective as of 1st January 2018. We analyse alternative models for probability of default (PD) estimation that are in accordance with IFRS 9. In our model, PD is dependent on idiosyncratic firm-specific factors and systematic macroeconomic conditions. In order to identify the macroeconomic conditions that affect PD, we fit a semi-parametric Cox Proportional Hazards model to default data in a similar fashion to Figlewski et al. (2012). Subsequently, in line with Chen et al. (2005) and Kim and Partington (2014), we use a SAS macro programme to calculate PDs. We found that the inclusion of macroeconomic covariates in the regression increases explanatory power and improves the regression results. The regression results were transformed into PDs and we calculated PDs for each business partner. With an 'Area Under the Curve' value of 0.87, our model is able to accurately predict the business partners that will default within the next 12 months. With this study, we present a good foundation for the implementation of a new model in line with IFRS 9.