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The impact of the COVID-19 crisis on bank credit risk management
Lukášková, Karolína ; Teplý, Petr (advisor) ; Jakubík, Petr (referee)
iv Abstract This diploma thesis examines the impact of the COVID-19 crisis on the bank credit risk in the European Union. The analysis is performed using two sets of panel data. The first set contains data at the bank-level between 2012 and 2018 and is obtained from BankFocus batabase and the second set of data is obtained from the EBA Risk dashboard and contains data at the country-level between 2014 and 2020. Both datasets contain bank-specific variables and macroeconomic variables. We use the variables Cost of risk, Total capital ratio, Tier 1 ratio and NPE ratio as dependent variables. As representatives of the COVID-19 shock, we use the number of people infected with this disease, the number of deaths from this disease and the Stringency Index. We employ the GMM system for our analysis and test 5 hypotheses. We did not reject 3 hypotheses, namely that Cost of risk is a key determinant of credit risk and that the crisis caused by COVID-19 affects the variables Capitalo ratio and NPE ratio. We further concluded that the variables representing COVID-19 do not have a negative effect on credit risk, mainly due to the interventions of the ECB and the IASB. JEL Classification C12, C33, G01, G21 Keywords bank, COVID-19 crisis, credit risk management, Stringency index Title Author's e-mail Supervisor's e-mail...
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The impact of the COVID-19 crisis on bank corporate credit risk management in the US and the UK
Kořínek, Matěj ; Teplý, Petr (advisor) ; Kraicová, Lucie (referee)
The thesis deals with bank corporate credit risk management during the COVID-19 crisis in the US and the UK. As a proxy of corporate credit risk, we employ corporate aggregate probability of default provided by Credit Benchmark. To measure the impact of the crisis on corporate aggregate probability of default, we use variables representing macroeconomic and financial market environments. Furthermore, as proxies for the COVID-19 shock and governments' fiscal measures, we employ COVID-19 stringency index and dummy variable(s), respectively. Our data set consists of 60 monthly observations, and by its structure is suitable for time series analysis. The analysis is based on Ordinary Least Squares, Two Stage Least Squares, and Generalized Method of Moments estimations. The results show that fiscal measures "artificially" decreased change of corporate aggregate probability of default in both countries. We recommend that the respective bank credit risk managers incorporate proxies representing fiscal measures in their estimation of through-the-cycle probability of default that serves as an input for calculating regulatory capital. Besides, a variable representing stringency index is found to be significant in the US's model. Thus, we recommend using such a proxy as input for stress testing in the US.
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