Please use this identifier to cite or link to this item: https://ah.nccu.edu.tw/handle/140.119/124935


Title: P2P借貸對於銀行績效影響
The Effects of P2P Lending on Bank Performance
Authors: 邵啟翔
Shao, Chi-Hsiang
Contributors: 何靜嫺
邵啟翔
Shao, Chi-Hsiang
Keywords: P2P借貸
銀行績效
P2P lending
Bank's performance
Date: 2019
Issue Date: 2019-08-07 16:48:18 (UTC+8)
Abstract: With the development of technology, some tech companies already use financial technology to provide financial services to the public like P2P platforms. Will the development of P2P impacts on banks performance? and whether different operation models of P2P will lead to a different result? In this paper, we contribute to this ongoing issue by analyzing banks efficiency and performance before and after P2P showing up in both U.S and UK. First, we find U.S. and UK small time deposits (deposits less than $100,000) in commercial banks went down after 2008 the time which P2P grew up. Second, according to our empirical results, P2P overall makes negative impacts on banking system in the U.S. but not in UK, because the business model of P2P in the U.S. is more like a traditional bank. The result shows that the appearance of P2P indeed brings about the change of people’s financial behavior in the U.S due to higher investment return for investors and lower borrowing cost for borrowers. People have more options to manage their money except saving at banks now, and it harms banks operation in that deposits and loans of banks gets lower than before. At the same time, however, input variables such as fixed assets and labors of banks are still growing, leading to bank efficiency and performance get worse than the time before P2P appearance. But there are also risks on P2P lending platforms such as default risk and the crackdown of P2P. Therefore, governments also have to monitor this issue. They can erect more restricted rules on P2P established, making sure that investors can have more protection.
Reference: Andries, A. M. (2011). The determinants of bank efficiency and productivity growth in the
Central and Eastern European banking systems. Eastern European Economics, 49(6), 38-59.

Bachmann, A., Becker, A., Buerckner, D., Hilker, M., Kock, F., Lehmann, M., ... & Funk, B. (2011). Online peer-to-peer lending-a literature review. Journal of Internet Banking and Commerce, 16(2), 1.

Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and
scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078-1092.

Bartlett, R. P., Morse, A., Stanton, R., & Wallace, N. (2017). Consumer lending discrimination in the Fintech era. UC Berkeley Public Law Research Paper.

Coelli, T. (1996). A guide to DEAP version 2.1: a data envelopment analysis (computer)
program. Centre for Efficiency and Productivity Analysis, University of New England,
Australia.

Das, A., Ray, S. C., & Nag, A. (2009). Labor-use efficiency in Indian banking: A branch-level analysis. Omega, 37(2), 411-425.

De Roure, Calebe and Pelizzon, Loriana and Tasca, Paolo (April 20, 2016). How Does P2P Lending Fit into the Consumer Credit Market?. Available at SSRN: https://ssrn.com/abstract=2756191 or http://dx.doi.org/10.2139/ssrn.2756191

Drake, L. (2001). Efficiency and productivity change in UK banking. Applied Financial Economics, 11(5), 557-571.

Einav, Liran, Mark Jenkins, and Jonathan Levin, The Impact of Information Technology on
Consumer Lending," RAND Journal of Economics, 2013, 44 (2), 249-274.

Emekter, R., Tu, Y., Jirasakuldech, B., & Lu, M. (2015). Evaluating credit risk and loan performance in online Peer-to-Peer (P2P) lending. Applied Economics, 47(1), 54-70.

Fenn, P., Vencappa, D., Diacon, S., Klumpes, P., & O.Brien, C. (2008). Market structure
and the efficiency of European insurance companies: A stochastic frontier analysis.
Journal of Banking & Finance, 32(1), 86-100.

Fiordelisi, F., Marques-Ibanez, D., & Molyneux, P. (2011). Efficiency and risk in European
banking. Journal of Banking & Finance, 35(5), 1315-1326.

Forster, J., & Shaffer*, S. (2005). Bank efficiency ratios in Latin America. Applied Economics Letters,
12(9), 529-532.
Hoff, A. (2007). Second stage DEA: Comparison of approaches for modelling the DEA score.
European Journal of Operational Research, 181(1), 425-435.

Mathisen, M. J., & Buchs, T. D. (2005). Competition and efficiency in banking: Behavioral evidence from Ghana (No. 5-17). International Monetary Fund.

Marcus, G. (2001). An approach to the consideration of bank merger issues by regulators: A South African case. BIS Papers, 4, 133-147.

Mathuva, D. M. (2009). Capital adequacy, cost income ratio and the performance of commercial
banks: the Kenyan scenario. The International journal of applied economics and Finance, 3(2),
35-47.

Mester, L. J. (1996). A study of bank efficiency taking into account risk-preferences. Journal of
banking & finance, 20(6), 1025-1045.

Milne, Alistair K. L. and Parboteeah, Paul (May 5, 2016). The Business Models and Economics of Peer-to-Peer Lending. ECRI Research Report, 2016, No 17. Available at SSRN: https://ssrn.com/abstract=2763682 or http://dx.doi.org/10.2139/ssrn.2763682

Li, S., Liu, F., Liu, S., & Whitmore, G. A. (2001). Comparative performance of Chinese
commercial banks: Analysis, findings and policy implications. Review of Quantitative
Finance and Accounting, 16(2), 149-170.

Liebscher, K. (2005). Overview of financial services in Austria. BIS Review, 47, 1-5.
Käfer, B. (2018). Peer-to-Peer Lending–A (Financial Stability) Risk Perspective. Review of Economics, 69(1), 1-25.

Kumar, S., & Gulati, R. (2008). An examination of technical, pure technical, and scale
efficiencies in Indian public sector banks using data envelopment analysis. Eurasian
Journal of Business and Economics, 1(2), 33-69.

Ozili, P. K. (2018). Impact of digital finance on financial inclusion and stability. Borsa Istanbul
Review, 18(4), 329-340.

Vives, X. (2017). The impact of FinTech on banking. European Economy, (2), 97-105.

Romānova, I., & Kudinska, M. (2016). Banking and Fintech: A challenge or opportunity?. In
Contemporary Issues in Finance: Current Challenges from Across Europe (pp. 21-35). Emerald
Group Publishing Limited.

Saleh, H., Lotfi, F. H., Eshlaghy, A. T., & Shafiee, M. (2011). A new two-stage DEA model for
bank branch performance evaluation. In 3rd National Conference on Data Envelopment
Analysis, Islamic Azad University of Firoozkooh.

Serrano-Cinca, C., & Gutiérrez-Nieto, B. (2016). The use of profit scoring as an alternative to credit scoring systems in peer-to-peer (P2P) lending. Decision Support Systems, 89, 113-122.

Tang, H. (2019). Peer-to-peer lenders versus banks: substitutes or complements? The Review of Financial Studies, 32(5), 1900-1938.

Wang, H., Chen, K., Zhu, W., & Song, Z. (2015). A process model on P2P lending. Financial
Innovation, 1(1), 3.

Wolfe, Brian and Yoo, Woongsun (March 30, 2018). Crowding Out Banks: Credit Substitution by Peer-To-Peer Lending. Available at SSRN: https://ssrn.com/abstract=3000593 or http://dx.doi.org/10.2139/ssrn.3000593

Yan, J., Yu, W., & Zhao, J. L. (2015). How signaling and search costs affect information
asymmetry in P2P lending: the economics of big data. Financial Innovation, 1(1), 19.

Yue, P. (1992). Data envelopment analysis and commercial bank performance: a primer with
applications to Missouri banks. IC² Institute Articles.

Yoon, Y., Li, Y., & Feng, Y. (2019). Factors affecting platform default risk in online peer-to-peer (P2P) lending business: an empirical study using Chinese online P2P platform data. Electronic Commerce Research, 1-28.
Description: 碩士
國立政治大學
經濟學系
106258006
Source URI: http://thesis.lib.nccu.edu.tw/record/#G0106258006
Data Type: thesis
Appears in Collections:[經濟學系] 學位論文

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