LAUSR

Abstract This paper proposes a method framework to estimate operational efficiencies and potential income gains considering the credit risk for banks. The method refers to the optimization of operational income, interest income, and non-performing loan amounts. As main innovations, potential interest income gains from credit technology improvement and loan provision reduction are detected. Operational capability restriction is considered by an inverse-like DEA model. Based on an empirical study of Chinese banks, some suggestions are obtained: (1) diverse operational efficiencies are observed for bank groups. Operational efficiencies of rural commercial banks became worse after going public. (2) For city-owned and rural commercial banks, the investment performance and financial services should be improved to increase operational incomes. Excessive loan provision should be cautious to forbid more non-performing loans. (3) Credit risk technology improvement should be addressed by state-owned and rural commercial banks. Their operational inefficiencies are mainly from weak credit risk control. Research Highlights A modified data envelopment analysis for output optimisation is proposed. Potential interest gains have been decomposed into parts for different causes. Operational capacity restrictions are considered in potential output estimations. The approach is applied to measure banks’ operational performance in China. Future suggestions for bank groups are provided in the empirical study.