Bankruptcy in Indian Private Sector Banks: A Neural Network Analysis

Authors

  • Surbhi Dhama Relationship Manager, Business Banking, IDFC First Bank, India

DOI:

https://doi.org/10.12725/ujbm.52.6

Keywords:

bankruptcy, neural network, prediction

Abstract

This paper aims to predict the bankruptcy in Indian private banks using financial ratios such as ROA, GNPA, EPS, PAT, and GNP of the country. This paper also explains the importance of Ohlson’s number, Graham’s number and Zmijewski number as the major predictors of bankruptcy while developing a model using neural networks. For the prediction, the financial data for private sector banks of India such as HDFC, HDFC, ICICI, AXIS, YES bank, KOTAK MAHINDRA Bank, FEDERAL BANK, INDUSIND Bank, RBL and KARUR VYSYA for the last 10 years from 2010-2019 have been analysed. The model developed during the research will help the financial institutions and banks in India to understand the economic condition of the banking industry.

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Published

2020-08-26

How to Cite

Dhama, S. . (2020). Bankruptcy in Indian Private Sector Banks: A Neural Network Analysis . Ushus Journal of Business Management, 19(3), 89-114. https://doi.org/10.12725/ujbm.52.6