Developing a Scoring Credit Model Based on the Methodology of International Credit Rating Agencies

Abstract

The purpose of this work is to examine the relationship of various financial and non-financial (qualitative) factors of performance of non-financial companies and their credit ratings.

We developed the scoring model which was based on the methodologies of international and Russian rating agencies. The modelled ratings of non-financial companies for 2018–2020 were compared with actual ratings assigned by the rating agencies and discrepancies were explained. The sample includes companies from retail, protein and agriculture, steel, oil and gas sectors from Russia, USA, Luxembourg, England, Canada, India, Ukraine and Brazil.

The paper proved that addition of business and environmental, social and governance factors improved the quality ofscoring models in comparison to those including only financial metrics. There are strong patterns in the resulting ratings of companies for some industries. Retail industry companies are associated with high sales indicators, while steel industry companies have high interest expenses coverage ratios. Oil and gas industry companies mostly show high results in reserves coefficients.

The study developed a credit rating forecasting tool that emulates the work of analysts of rating agencies and therefore has a high predictive power. The developed model can be used by financial market practitioners to predict the credit ratings of Russian companies in the face of the refusal of international rating agencies to rate Russian issuers.