The Development and Validation of Rating Model for Insurance Companies

In this study, we analyzed the determinants of insolvency for Russian insurance companies. The relevance of the paper is underpinned by strong interest of investors to emerging insurance industry due to their strong growth. But this growth comes with elevated risk. Thus, identification of key drivers of insurance companies’ insolvency risk is the critical task there. Literature review indicated that there are only a few studies at this topic. Logistic regression was chosen as the modeling method. The dataset included financial and non-financial factors of 161 Russian insurance companies over the period 2013-2019. The key financial drivers of credit risks of Russian insurance companies were profitability, liquidity of assets and premium collection discipline. Among non-financial factors efficiency of strategic management, management of sales channels, regional diversification of business and credit quality of reinsurers were significant. Macroeconomic variables such as insurance penetration and inflation are also important drivers of insurance companies’ creditworthiness. The model had good discriminative and predictive power (accuracy ratio of 0.9 and KS statistics of 0.6). We also compared these drivers with those in advanced markets and analyzed similarities and differences. Lastly, we developed the rating system consisting of 17 rating grades and estimated probability of default for each grade. Results of statistical tests confirmed the correctness of calibration of the rating system, stability of the population and good distribution of observations within the rating scale. The rating system can be used by financial institutions, rating agencies or regulators to assess and monitor of credit quality of insurance companies in Russia.