Analysis and Forecasting of Credit Institutions Bankruptcy Using Neural Network Modeling

Abstract

. This work is devoted to the study of the probabilistic bankruptcy state of Russian Federation credit institutions. It develops a tool (neural network) designed to assess the financial condition (bankruptcy) of banks. Data collection and generalization are carried out, the results of numerical modeling are shown. The neural network is created and optimized with the help of collected training sample. Subsequently, several tasks related to the assessment of financial condition are solved. The work has an applied nature, as the results can be useful for credit institutions of the Russian Federation