Impact of fintech on commercial banks’ efficiency: Evidence from China

This paper examines the overall technical efficiency, pure technical efficiency and scale efficiency of 15 Chinese commercial banks from 2015 to 2020. The DEA model is used to draw the conclusion: the efficiency of state-owned commercial banks is lower than joint-stock commercial banks and city comm...

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Main Author: Xu, Xingyu
Format: Dissertation (University of Nottingham only)
Language:English
Published: 2022
Online Access:https://eprints.nottingham.ac.uk/68222/
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author Xu, Xingyu
author_facet Xu, Xingyu
author_sort Xu, Xingyu
building Nottingham Research Data Repository
collection Online Access
description This paper examines the overall technical efficiency, pure technical efficiency and scale efficiency of 15 Chinese commercial banks from 2015 to 2020. The DEA model is used to draw the conclusion: the efficiency of state-owned commercial banks is lower than joint-stock commercial banks and city commercial banks. Then, the Tobit regression model is used to empirically study the influence of various possible factors in financial technology on the efficiency of commercial banks. It is found that the proportion of people with a master's degree or above, the growth rate of third-party Internet payment, M2 growth rate, capital adequacy ratio and bank market share are significantly positively correlated with the efficiency of commercial banks. In contrast, the non-performing loan ratio and mobile banking customer growth rate are negatively correlated with the efficiency of commercial banks. However, GDP growth rate, CPI growth rate, return on equity and asset-liability ratio have no significant correlation with the efficiency of commercial banks. Finally, this paper puts forward some measures to improve the efficiency of China's commercial banks.
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spelling nottingham-682222023-05-02T10:46:11Z https://eprints.nottingham.ac.uk/68222/ Impact of fintech on commercial banks’ efficiency: Evidence from China Xu, Xingyu This paper examines the overall technical efficiency, pure technical efficiency and scale efficiency of 15 Chinese commercial banks from 2015 to 2020. The DEA model is used to draw the conclusion: the efficiency of state-owned commercial banks is lower than joint-stock commercial banks and city commercial banks. Then, the Tobit regression model is used to empirically study the influence of various possible factors in financial technology on the efficiency of commercial banks. It is found that the proportion of people with a master's degree or above, the growth rate of third-party Internet payment, M2 growth rate, capital adequacy ratio and bank market share are significantly positively correlated with the efficiency of commercial banks. In contrast, the non-performing loan ratio and mobile banking customer growth rate are negatively correlated with the efficiency of commercial banks. However, GDP growth rate, CPI growth rate, return on equity and asset-liability ratio have no significant correlation with the efficiency of commercial banks. Finally, this paper puts forward some measures to improve the efficiency of China's commercial banks. 2022-01-24 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/68222/1/20224164_BUSI4153_2021_22.pdf Xu, Xingyu (2022) Impact of fintech on commercial banks’ efficiency: Evidence from China. [Dissertation (University of Nottingham only)]
spellingShingle Xu, Xingyu
Impact of fintech on commercial banks’ efficiency: Evidence from China
title Impact of fintech on commercial banks’ efficiency: Evidence from China
title_full Impact of fintech on commercial banks’ efficiency: Evidence from China
title_fullStr Impact of fintech on commercial banks’ efficiency: Evidence from China
title_full_unstemmed Impact of fintech on commercial banks’ efficiency: Evidence from China
title_short Impact of fintech on commercial banks’ efficiency: Evidence from China
title_sort impact of fintech on commercial banks’ efficiency: evidence from china
url https://eprints.nottingham.ac.uk/68222/