To evaluate the efficiency of decision-making units, researchers continually develop models simulating the production process of organizations. This study formulates a network model integrating undesirable outputs to measure the efficiency of Vietnam’s banking industry. Employing methodologies from the data envelopment analysis (DEA) approach, the efficiency scores for these banks are subsequently computed and comparatively analyzed. The empirical results indicate that the incorporation of undesirable output variables in the efficiency evaluation model leads to significantly lower efficiency scores compared to the conventional DEA model. In practical terms, the study unveils a deterioration in the efficiency of banking operations in Vietnam during the post-Covid era, primarily attributed to deficiencies in credit risk management. These findings contribute to heightening awareness among bank managers regarding the pivotal importance of credit management activities.

This study analyzes the influence of five primary factors—inflation, capital ratio, deposits, non-performing loans, and bank size—on the performance of banks in Vietnam. Our sample encompasses 26 commercial banks from 2014 to 2023. The analysis incorporates data sourced from commercial banks’ financial statements and annual reports. Our findings indicate that banks with higher capital ratios and sizes generally exhibit superior performance. Moreover, inflation positively influences the performance of Vietnamese commercial banks throughout the selected timeframe. In contrast, non-performing loans and deposits are inverse to bank performance. Our findings offer novel insights into the factors influencing bank performance in a growing economy like Vietnam, along with recommendations for Vietnamese commercial banks and the State Bank of Vietnam to implement effective methods to improve bank performance.