Developing a Model Estimating the Probability of Insurance Companies' Bancruptcy

Nowadays, insurance market in Russia is not as developed as in western countries. One of the reasons of it is the low credibility of citizens which is caused by uncertainty over the future of insurance companies. This could be improved by creating a model that could be used for estimating the probability of insurer’s failure. It is common knowledge that a lot of researchers work on the problem of corporate bankruptcies. There are plenty of models, created to estimate the probability of failures of firms. Some models deal with companies from the whole market, others predict failures for market segments. The question is how to predict bankruptcies of Russian insurers and choose the most reliable underwriter. A lot of research is done in the field of bankruptcies’ early warning, but the amount of studies, devoted to insurers is extremely small. Moreover, almost nothing is said in literature about Russian insurance firms’ insolvency prediction. That is why we develop a model that can be used for predicting bankruptcies for Russian insurers. Logistic Regression Analysis is used and the model bases both on conventional financial ratios and non-conventional factors – inherent ratios for Russian insurers. We believe that this study will be useful in case of early warning for bankruptcy risk of Russian insurance firms.