Forecasting loan default rates using macroeconomic variables

Abstract

The aim of this thesis is to model and forecast Estonian loan default rates using macroeconomic variables. Debt portfolio analysis and forecasting are important parts of credit risk management and are used in capital planning, risk assessment and scenario analysis. The selection of the final model and its suitability with the financial supervisors are discussed, highlighting the pros and cons of machine learning and simpler statistical models. The thesis also highlights the real-life value of default rate forecasting and describes its usage from the perspective of an Estonian bank - Coop Pank.