Credit ratings and Risk Estimation: Will in Work in Russia?

The topic of my research is “Methods of Credit Risk Estimation: will it work in Russia?”. The main purpose of this paper is to analyze the existing methods of credit risk estimation, test some of them, detect advantages and drawbacks and understand whether these methods can work within Russian financial market. Credit risk is a possibility of losses driven by a failure of counterparty to fulfill liabilities. For the creditor results of this failure are measured by losing principle and interest income less amount already received. Empirical part of the study is the analysis of the methodology used in the bank “…” (name is hidden for the purpose of confidentiality). Relying on the database, which stored the information about 16 financial ratios of 75 companies, linear econometric model was produced. Using Stata tools, we chose 6 the most significant ratios, which influenced the potential status of the borrower – profitability, working capital ratio, receivables to payables ratio, payables turnover, inventory turnover, finished goods turnover. Judging by the main econometric indicators of regression quality, such as R2-adjusted and R2 - reliability of the model turned out to be high. For comparison having used the same database, we build a regression taking into account the coefficients offered by a bank technique. This regression was much weaker, and 2 out of 5 coefficients got negative weights (current ratio, profitability), that doesn't correspond to the economic logic. All things considered, the present study demonstrates that evaluation of credit risks is one of the most crucial problems for credit organizations. It goes without saying that effective credit risk estimation brings to higher stability in credits return process, which in turn results in higher profitability and respectable status of credit organization. Hence, banks make an effort to build relatively simple model to estimate credit risk, which can be used for different sets of data.