Measuring the Determinants for the Survival of Indian Banks Using Machine Learning Approach

Santosh Kumar Shrivastav

FIIB Business Review, 2019, vol. 8, issue 1, 32-38

Abstract: Abstract Banks’ survival is often seen as a crucial role in the financial system and the economy. Without a sound and effective banking system, no country can ever have a healthy economy. This research article concentrates on the analysis of collected data for the failed and surviving private and public banks working in India. All possible bank-specific variables as well as macroeconomic and market structure variables have been used to understand the important factors accountable for the survival of the Indian banks through feature selection methods. The Output of the feature selection method shows that, the important factors for bank’s failure or survival are z-score, return on net worth, profit after tax, return on assets, equity, overheads, total assets, income, loan, inflation CPI, interest on revenue, liabilities and GDP growth.

Keywords: Survival analysis; feature selection method; filter method; financial statements; ranking method (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:fbbsrw:v:8:y:2019:i:1:p:32-38

DOI: 10.1177/2319714519825939

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