Assessment of Credit Risk Management Efficiency in Banking Industry with DEA and Logit Model

Xiaoshan Feng

Doctoral thesis

Abstract:

Uncertainty in global financial markets is rising in the complex external shocks such as post-epidemic phase and the ongoing energy crisis, the collapse of two U.S. banks. Under the current circumstance, European economies are in recession after suffering from the impacts of the Russia-Ukraine conflict, which plunged them into an inflationary crisis. Central banks are implementing rate hikes to curb inflation. However, the mutual relationship between macroeconomy and credit risk leads to a greater challenge to the commercial banks. Coupled with higher corporate financing costs, default probabilities are expected to increase in the near future. Therefore, the banking industry should not only resist external shocks but should also strengthen the assessment and inspection of its internal credit risk management capabilities. The objective of this dissertation is to examine how efficiency of credit risk management is influenced by the macroeconomic and bank specific determinants for selected banking industries in Central Europe. By using DEA model, we measure the credit risk management efficiency of selected five central European banking industries from 2012-2021, investigate the productivity change in each country by applying Malmquist index. Then determine the factors that contribute to effective credit risk management for particular banking industries by logistic regression analysis. Eventually, provide a general performance evaluation of selected European banking industries on credit risk management. In selected European banking industries, domestic-owned banks have better credit risk management efficiency than foreign-owned banks, mid-size banks show better efficiency results. In addition, European banking industries can be concluded that have productivity change, and the frontier-shift effect is the primary accountable factor. The logistic regression result emphasized the probability of banks acting efficient on credit risk management increasing with the larger size, more conservative risk appetite and more use of IRB approach to calculate RWAs for credit risk exposures. Besides, the finding also proved that apart from the macroeconomic development, own risk governance and business strategy are more crucial to better credit risk management. But the effect of stricter regulation varies from bank to bank.

Abstract:

Uncertainty in global financial markets is rising in the complex external shocks such as post-epidemic phase and the ongoing energy crisis, the collapse of two U.S. banks. Under the current circumstance, European economies are in recession after suffering from the impacts of the Russia-Ukraine conflict, which plunged them into an inflationary crisis. Central banks are implementing rate hikes to curb inflation. However, the mutual relationship between macroeconomy and credit risk leads to a greater challenge to the commercial banks. Coupled with higher corporate financing costs, default probabilities are expected to increase in the near future. Therefore, the banking industry should not only resist external shocks but should also strengthen the assessment and inspection of its internal credit risk management capabilities. The objective of this dissertation is to examine how efficiency of credit risk management is influenced by the macroeconomic and bank specific determinants for selected banking industries in Central Europe. By using DEA model, we measure the credit risk management efficiency of selected five central European banking industries from 2012-2021, investigate the productivity change in each country by applying Malmquist index. Then determine the factors that contribute to effective credit risk management for particular banking industries by logistic regression analysis. Eventually, provide a general performance evaluation of selected European banking industries on credit risk management. In selected European banking industries, domestic-owned banks have better credit risk management efficiency than foreign-owned banks, mid-size banks show better efficiency results. In addition, European banking industries can be concluded that have productivity change, and the frontier-shift effect is the primary accountable factor. The logistic regression result emphasized the probability of banks acting efficient on credit risk management increasing with the larger size, more conservative risk appetite and more use of IRB approach to calculate RWAs for credit risk exposures. Besides, the finding also proved that apart from the macroeconomic development, own risk governance and business strategy are more crucial to better credit risk management. But the effect of stricter regulation varies from bank to bank.

Keywords

Credit risk management, Size, Risk appetite, AHP, Data envelopment analysis, Logistic regression model, Commercial banks, Central European

Keywords

Credit risk management, Size, Risk appetite, AHP, Data envelopment analysis, Logistic regression model, Commercial banks, Central European

Language used: English

Date on which the thesis was submitted / produced: 3. 7. 2023

Thesis defence

• Date of defence: 11. 9. 2023
• Supervisor: Tomáš Tichý
• Reader: Monika Wieczorek-Kosmala, Jiří Witzany, Pavla Klepková Vodová

VSB – Technical University of Ostrava

Ekonomická fakulta

Doctoral programme:
Finance