The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.
Does fintech innovation improve bank efficiency? Evidence from China’s banking industry
Abstract
Abstract This paper examines whether the development of the financial technology (fintech) industry affects cost efficiency and the technology adopted for China's banking industry over the period 2003–2017. Different from previous works, we first construct fintech industry development indices for fintech overall and then four subcategories by using fintech enterprise-level data and measure the relevant efficiency scores for Chinese banks under different ownership structures by applying the stochastic metafrontier approach. Our results show that state-owned commercial banks have the lowest cost efficiency and operate under inferior technology. When considering the influence of fintech development, we find that fintech innovations not only improve the cost efficiency of banks, but also enhance the technology used by banks. This double beneficial effect is more significant in the case of market support service innovations.
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Battese, G. E., & Coelli, T. J. (1995) · Empirical Economics · doi:10.1007/bf01205442 · Cited by 5,978
Deciphering the Liquidity and Credit Crunch 2007–2008
Brunnermeier, M. K. (2009) · Journal of Economic Perspectives · doi:10.1257/jep.23.1.77 · Cited by 3,322
Bresnahan, T. F., Brynjolfsson, E., & Hitt, L. M. (2002) · The Quarterly Journal of Economics · doi:10.1162/003355302753399526 · Cited by 3,211
In Search of Complementarity in Innovation Strategy: Internal R&D and External Knowledge Acquisition
Cassiman, B., & Veugelers, R. (2006) · Management Science · doi:10.1287/mnsc.1050.0470 · Cited by 2,490
Inside the black box: What explains differences in the efficiencies of financial institutions?
Berger, A. N., & Mester, L. J. (1997) · Journal of Banking & Finance · doi:10.1016/s0378-4266(97)00010-1 · Cited by 2,276
Fintech, regulatory arbitrage, and the rise of shadow banks
Buchak, G., Matvos, G., Piskorski, T., & Seru, A. (2018) · Journal of Financial Economics · doi:10.1016/j.jfineco.2018.03.011 · Cited by 1,784
Fintech: Ecosystem, business models, investment decisions, and challenges
Lee, I., & Shin, Y. J. (2018) · Business Horizons · doi:10.1016/j.bushor.2017.09.003 · Cited by 1,692
Computing Productivity: Firm-Level Evidence
Brynjolfsson, E., & Hitt, L. M. (2003) · Review of Economics and Statistics · doi:10.1162/003465303772815736 · Cited by 1,441
Battese, G. E., Rao, D. S. P., & O'Donnell, C. J. (2004) · Journal of Productivity Analysis · doi:10.1023/b:prod.0000012454.06094.29 · Cited by 1,274
The Role of Technology in Mortgage Lending
Fuster, A., Plosser, M., Schnabl, P., & Vickery, J. (2019) · The Review of Financial Studies · doi:10.1093/rfs/hhz018 · Cited by 1,128
Cited by
Hard and soft skill needs: Higher education and the Fintech sector
Doherty, O., & Stephens, S. (2023) · Journal of Education and Work · doi:10.1080/13639080.2023.2174954 · Cited by 39
Bolfek, M., & Lu, K. (2026) · Fintech and Digital Accounting Review · doi:10.1108/fdar-10-2025-0038
Metadata
- Authors
- Lee, C.-C., Li, X., Yu, C.-H., & Zhao, J.
- Venue
- International Review of Economics & Finance
- Publisher
- Elsevier BV
- Published
- 2021-07
- Volume
- 74
- Pages
- 468-483
- ISSN
- 1059-0560 (ISSN-L)
- OpenAlex
- W3137223397
- Cited by
- 544
- References
- 54
- FWCI
- 74.85
- Type
- journal article
- Language
- en
- Open access
- closed
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- Lee, C.-C., Li, X., Yu, C.-H., & Zhao, J. (2021). Does fintech innovation improve bank efficiency? Evidence from China’s banking industry. International Review of Economics & Finance. https://doi.org/10.1016/j.iref.2021.03.009
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