Forecasting of Revocation of Banking License Based on Disclosed Financial Statements

Since the Russian Central Bank have revoked about 200 banking licenses during last two years, the issue of forecasting of banking license revocation is of utmost social concern. The subject of this study is the banking sector of the Russian Federation. The subject of the study is the decision-making process for revoking banking licenses. Goal: To develop a model that helps to estimate the probability of revoking a banking license, taking into account the financial performance of the bank. In the first chapter, legislation in the banking sector was studied. As a result, the reasons for license revocation related to unsatisfactory financial condition were identified. An analysis of Russian banking sector was performed. Also, experts' opinions on the revocation of banking licenses in the Russian Federation were summarized. In addition, a review of the works devoted to forecasting of the bankruptcy of enterprises and banks was presented. In the second chapter, a model for estimating the probability of revoking a banking license was developed on the basis of the model of V.V. Kovalev. The financial indicators used in the model were investigated. Steps were proposed to modify the model based on real data. The capabilities of IBM SPSS Statistics in the implementation of these steps were described. The third chapter is devoted to the description of the achieved results. At the beginning of the chapter, limitations and assumptions, connected with the issue of estimating of probability of license revocation, were formulated. The data on banks was collected and described, including the financial indicators and the reasons for revoking licenses from these banks were used. Based on the statistics on the banks included in the sample, the model was modified in accordance with the three highlighted stages of the modification. An assessment of the quality of the developed model was given, and further prospects for research were proposed.