Development of the ‘Inner Assessment Model’ of Long-Term Default Probability for Corporate Borrowers in the Trade Segment of the Economy in Accordance with IFRS 9

Abstract

This work is the next step in the research project of various authors in modeling credit risk for Russian banks, taking into account the requirements of IFRS 9. This standard has been implemented all over the world since January 1, 2018 (including in the Russian banking market), and in accordance with the relevant standards it is necessary to clarify the existing models for assessing credit risk. IFRS 9 is based on the expected credit loss (ECL) approach. This new business model radically changes the approach to reserves under the rules of IFRS 9, including the impact of macroeconomic indicators on reserve value.   The purpose of this article is to create a model for assessing the probability of default for corporate borrowers in the trade ‘industry’ over the course of the whole life duration of assets, in accordance with the requirements of IFRS 9.   In this paper, the life-time probability of default of a financial instrument (referred to as life-time PD, or Lt PD) is based on a parametric model, and two distinct classes of distributions (the two-parameter Weibull distribution and the modified Weibull distribution) were studied. The results of model development are presented in this report.   The development of the model in this paper is based on real bank data, so the results and methods used in this work can be applied by both commercial banks and regulatory authorities to model and implement the various requirements of IFRS 9. The practical value of this research also determines its scientific novelty, since this research is one of the first studies in the field of long-term probability of default using real data from Russian corporate clients of commercial banks.