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The purpose of this study is to evaluate the effectiveness of 85 Russian banks (2016 - 2017). The study uses a manufacturing-oriented Data Envelopment Analysis (DEA) approach with financial ratios to measure bank performance. The study also uses multiple regression analysis to determine the variables that will be entered as inputs and outputs into the model (DEA). The research inputs include five main types of financial risk: interest rate risk, foreign currency risk, liquidity risk, credit risk and operational risk. In addition to the financial leverage, which is the sixth input. As for the results, they include net interest margin, return on assets, return on equity (ROE). The study showed that by the size of banks, banks achieved average efficiency as follows: large banks (76%), medium banks (85%) and small banks (88%). In other words, small banks were more efficient, while medium banks were more efficient than large banks. That is, large banks were the least effective in comparison with other banks. The study concluded that bank performance assessment should not be based on traditional ratios, which depend on profitability. Bank performance should be based on several key factors, namely risk, leverage, profitability, and competition, and DEA is an effective measurement tool for this comparison.
Keywords:risk, efficiency, financial ratios, data envelopment analysis (DEA), banking evaluation, leverage, competition, profitability, Russian banks.
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