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Resistance of commercial banks to the crisis caused by the COVID-19 pandemic: the case of Poland

126 citations0/0 files storedEquilibrium Quarterly Journal of Economics and Economic Policy

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Banking stability, regulation, efficiency Banking Sector Performance and Management Banking, Crisis Management, COVID-19 Impact

Abstract

Research background: The analysis allows to assess the impact of the industry structure of the credit portfolio on the resistance of commercial banks to the crisis resulting from the COVID-19 pandemic. It uses two independent methods to measure the impact of the pandemic on industry risk and the methodology allowing to prioritize industries in terms of potential negative effects of the crisis. Purpose of the article: The aim of the research is to assess the resilience of commercial banks operating in the Polish banking sector to the potential effects caused by the COVID-19 pandemic. The diagnostic features of 13 commercial banks were selected for its implementation. Methods: Two linear ordering methods were used, namely the Hellwig method and the TOPSIS method. The following were used as the criteria for parametric assessment of the resilience of commercial banks: capital adequacy, liquidity level, profitability of business activity, share in the portfolio of exposures with recognized impairment and the resilience of the bank's credit portfolio to the risk resulting from the exposure in economic sectors. These sectors were classified according to the level of risk associated with the effects of the crisis caused by the COVID-19 pandemic. Findings & Value added: The study allows to conclude that the largest banks conducting their operations in Poland are the most resistant ones to the consequences of the pandemic. At the same time, the banks most vulnerable due to the crisis were identified. The conclusions can be used, inter alia, in the process of managing the financial system stability risk and contribute to the discussion on the impact of the pandemic on the condition of commercial banks in emerging markets.

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References

1981Multiple Attribute Decision Making: Methods and Applications 1981Methods for Multiple Attribute Decision Making 2007The black swan: the impact of the highly improbable 2020COVID-19 and finance: Agendas for future research 2020The Global Macroeconomic Impacts of COVID-19: Seven Scenarios 2004Comparison of weights in TOPSIS models 1999A subjective and objective integrated approach to determine attribute weights 1982An Experimental Comparison of Different Approaches to Determining Weights in Additive Utility Models

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