Point in time probability of default modeling for international financial standards - a Turkish bank case study

Point in time probability of default modeling plays a crucial role in the context of International Financial Reporting Standards 9 (IFRS 9), which expects the measurement and recognition of expected credit losses (ECL) for financial instruments. IFRS 9 introduces a forward-looking approach, necessitating the estimation of one-year and lifetime PDs to capture credit risk over the entire expected life of financial assets. This thesis presents an in-depth analysis of PiT PD modeling in the framework of IFRS 9, highlighting its significance, methodologies, and implications for financial institutions. A case study of a Turkish Bank examined and established an autoregressive macroeconomic model to forecast the default rate (DR) of small and medium enterprise loan segments using the autoregressive linear model (ARLM) method. Results indicate that interest rates positively affect DR, and the USD-TRY exchange rate negatively affects DR. A basic quantitative validation of the DR model is implemented, and the forecast power of the DR model is examined by using out of time (OOT) period of DR. Finally, forward PDs for 10 years are calculated using adjusted Weibull distribution. Forward PDs are calibrated with the result of the ARLM model forecast under different scenarios. Thus, an applicable PiT PD term structure for SME portfolio is created.