Analysis and Forecasting of Credit Institutions Bankruptcy Using Neural Network Modeling
- https://doi.org/10.2991/aebmr.k.200312.260How to use a DOI?
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.
- © 2020, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - V P Pervadchuk AU - D B Vladimirova AU - A A Yudin PY - 2020 DA - 2020/03/17 TI - Analysis and Forecasting of Credit Institutions Bankruptcy Using Neural Network Modeling BT - Proceedings of the International Scientific Conference "Far East Con" (ISCFEC 2020) PB - Atlantis Press SP - 1865 EP - 1869 SN - 2352-5428 UR - https://doi.org/10.2991/aebmr.k.200312.260 DO - https://doi.org/10.2991/aebmr.k.200312.260 ID - Pervadchuk2020 ER -