Share:


Peer-to-peer lending (P2P) as disruptive, but complementary in Covid-19 exogenous shock

    Cliff Kohardinata   Affiliation
    ; Novrys Suhardianto   Affiliation
    ; Bambang Tjahjadi   Affiliation

Abstract

The purpose of this study is to examine the effect of P2P lending on bank credit in each type/segment of banking credit consisting of working capital credit, investment credit, and consumer credit in the period before and during the occurrence of the Covid-19 exogenous shock. Examining the effect of P2P lending on various types of bank loans is important because there is no conclusive evidence of whether P2P lending substitutes or complements various conventional bank loans. The Covid-19 pandemic impairs the income of many people and accelerates the use of digital technology in most daily activities including banking. Due to economic contraction during the outbreak, the government requires banks to relax the loan covenants. Therefore, P2P lending that provides flexibility might complement bank loans during the Covid-19 pandemic. The test in this study uses panel regression and is carried out by separating the period before (July 2019–March 2020), and during (July 2020–March 2021) the Covid-19 pandemic. The results show that P2P lending was disruptive for bank loans before the pandemic and turned to be complementary during the pandemic, it might be due to P2P lending flexibility complementing the bank credit relaxation during the pandemic.

Keyword : P2P lending, banking, FinTech, disruptive innovation, exogenous shock, Covid-19, substitution, complement

How to Cite
Kohardinata, C., Suhardianto, N., & Tjahjadi, B. (2024). Peer-to-peer lending (P2P) as disruptive, but complementary in Covid-19 exogenous shock. Business: Theory and Practice, 25(1), 241–251. https://doi.org/10.3846/btp.2024.16584
Published in Issue
Apr 30, 2024
Abstract Views
381
PDF Downloads
251
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Aaker, D. A., & Keller, K. L. (1990). Consumer evaluations of brand extensions. Journal of Marketing, 54(1), 27–41. https://doi.org/10.2307/1252171

Anagnostopoulos, I. (2018). Fintech and regtech: Impact on regulators and banks. Journal of Economics and Business, 100, 7–25. https://doi.org/10.1016/j.jeconbus.2018.07.003

Brown, R. S., & Kline, W. A. (2020). Exogenous shocks and managerial preparedness: A study of U.S. airlines’ environmental scanning before the onset of the COVID-19 pandemic. Journal of Air Transport Management, 89(June), 1–9. https://doi.org/10.1016/j.jairtraman.2020.101899

Chandler, J. A., Short, J. C., & Wolfe, M. T. (2021). Finding the crowd after exogenous shocks: Exploring the future of crowdfunding. Journal of Business Venturing Insights, 15(March), 1–6. https://doi.org/10.1016/j.jbvi.2021.e00245

Chauhan, Y., & Kumar, S. B. (2019). Does accounting comparability alleviate the informational disadvantage of foreign investors? International Review of Economics and Finance, 60 December 2018, 114–129. https://doi.org/10.1016/j.iref.2018.12.018

Christensen, C. M. (1997). Innovator’s dilemma. Harvard Business School Press.

Christensen, C. M., McDonald, R., Altman, E. J., & Palmer, J. E. (2018). Disruptive innovation: An intellectual history and directions for future research. Journal of Management Studies, 55(7), 1043–1078. https://doi.org/10.1111/joms.12349

Christensen, C. M., Raynor, M., & McDonald, R. (2015). What is disruptive innovation? Harvard Business Review, December.

Dang, V. D. (2019). The effects of loan growth on bank performance: Evidence from Vietnam. Management Science Letters, 9, 899–910. https://doi.org/10.5267/j.msl.2019.2.012

Doan, T., Nguyen, S., Vu, H., Tran, T., & Lim, S. (2015). Does rising import competition harm local firm productivity in less advanced economies? Evidence from the Vietnam’s manufacturing sector. The Journal of International Trade & Economic Development, May, 25(1), 37–41. https://doi.org/10.1080/09638199.2015.1035739

Fu, J., & Mishra, M. (2022). Fintech in the time of COVID-19: Technological adoption during crises. Journal of Financial Intermediation, 50, 1–30. https://doi.org/10.1016/j.jfi.2021.100945

Goldstein, I., Jiang, W., & Karolyi, G. A. (2019). To FinTech and beyond. Review of Financial Studies, 32(5), 1647–1661. https://doi.org/10.1093/rfs/hhz025

Gomber, P., Koch, J.-A., & Siering, M. (2017). Digital finance and FinTech: Current research and future research directions. Journal of Business Economics, 87(5), 537–580. https://doi.org/10.1007/s11573-017-0852-x

Hasan, R., Ashfaq, M., & Shao, L. (2021). Evaluating drivers of Fintech adoption in the Netherlands. Global Business Review, 1–14. https://doi.org/10.1177/09721509211027402

Hoechle, D. (2007). Robust standard errors for panel regressions with cross-sectional dependence. Stata Journal, 7(3), 281–312. https://doi.org/10.1177/1536867X0700700301

Jagtiani, J., & John, K. (2018). Fintech: The impact on consumers and regulatory responses. Journal of Economics and Business, 100, 1–6. https://doi.org/10.1016/j.jeconbus.2018.11.002

Jagtiani, J., & Lemieux, C. (2018). Do fintech lenders penetrate areas that are underserved by traditional banks? Journal of Economics and Business, 100(March), 43–54. https://doi.org/10.1016/j.jeconbus.2018.03.001

Jiang, C., Xu, Q., Zhang, W., Li, M., & Yang, S. (2018). Does automatic bidding mechanism affect herding behavior? Evidence from online P2P lending in China. Journal of Behavioral and Experimental Finance, 20, 39–44. https://doi.org/10.1016/j.jbef.2018.07.001

Kohardinata, C., Soewarno, N., & Tjahjadi, B. (2020a). Indonesian peer to peer lending (P2P) at entrant’s disruptive trajectory. Business: Theory and Practice, 21(1), 104–114. https://doi.org/10.3846/btp.2020.11171

Kohardinata, C., Suhardianto, N., & Tjahjadi, B. (2020b). Peer-to-peer lending platform: From substitution to complementary for rural banks. Business: Theory and Practice, 21(2), 713–722. https://doi.org/10.3846/btp.2020.12606

Kuckertz, A., Brändle, L., Gaudig, A., Hinderer, S., Morales Reyes, C. A., Prochotta, A., Steinbrink, K. M., & Ber­ger, E. S. C. (2020). Startups in times of crisis – A rapid response to the COVID-19 pandemic. Journal of Business Venturing Insights, 13(April). https://doi.org/10.1016/j.jbvi.2020.e00169

Lee, I., & Shin, Y. J. (2018). Fintech: Ecosystem, business models, investment decisions, and challenges. Business Horizons, 61(1), 35–46. https://doi.org/10.1016/j.bushor.2017.09.003

Levin, J., & Milgrom, P. (2004). Consumer theory. https://web.stanford.edu/~jdlevin/Econ 202/Consumer Theory.pdf

Liu, J., Li, X., & Wang, S. (2020). What have we learnt from 10 years of fintech research? A scientometric analysis. Technological Forecasting and Social Change, 155(March), 1–12. https://doi.org/10.1016/j.techfore.2020.120022

Ma, L., Zhao, X., Zhou, Z., & Liu, Y. (2018). A new aspect on P2P online lending default prediction using meta-level phone usage data in China. Decision Support Systems, 111(November 2017), 60–71. https://doi.org/10.1016/j.dss.2018.05.001

Miyajima, K. (2020). What influences bank lending in Saudi Arabia? Islamic Economic Studies, 27(2), 125–155. https://doi.org/10.1108/IES-07-2019-0018

Montgomery, N., Squires, G., & Syed, I. (2018). Disruptive potential of real estate crowdfunding in the real estate project finance industry A literature review. Property Management, 36(5), 597–619. https://doi.org/10.1108/PM-04-2018-0032

Nguyen, T. Le, Vu Van, H., Nguyen, L. D., & Tran, T. Q. (2017). Does rising import competition harm Vietnam’s local firm employment of the 2000s? Economic Research, 30(1), 1882–1895. https://doi.org/10.1080/1331677X.2017.1392883

Otoritas Jasa Keuangan. (2018). Ikhtisar Data Keuangan Fintech (Peer To Peer Lending) Periode Desember 2018. OJK.

Otoritas Jasa Keuangan. (2020a). Ikhtisar Data Keuangan Fintech (Peer To Peer Lending) Periode Desember 2020. OJK.

Otoritas Jasa Keuangan. (2020b). Perkembangan Fintech lending Desember 2020. OJK.

Phan, D. H. B., Narayan, P. K., Rahman, R. E., & Hutabarat, A. R. (2019). Do financial technology firms influence bank performance? Pacific-Basin Finance Journal, 62, 1–13. https://doi.org/10.1016/j.pacfin.2019.101210

Ryu, H.-S. (2018). What makes users willing or hesitant to use Fintech?: the moderating effect of user type. Industrial Management and Data Systems, 118(3), 541–569. https://doi.org/10.1108/IMDS-07-2017-0325

Shawtari, F. A. M. (2018). Ownership type, bank models, and bank performance: The case of the Yemeni banking sector. International Journal of Productivity and Performance Management, 67(8), 1271–1289. https://doi.org/10.1108/IJPPM-01-2018-0029

Soluk, J., Kammerlander, N., & De Massis, A. (2021). Exogenous shocks and the adaptive capacity of family firms: Exploring behavioral changes and digital technologies in the COVID-19 pandemic. R&D Management, 51(4), 364–380. https://doi.org/10.1111/radm.12471

Stern, C., Makinen, M., & Qian, Z. (2017). FinTechs in China – with a special focus on peer to peer lending. Journal of Chinese Economic and Foreign Trade Studies, 10(3), 215–228. https://doi.org/10.1108/JCEFTS-06-2017-0015

Tang, H. (2019). Peer-to-Peer lenders versus banks: Substitutes or complements? Review of Financial Studies, 32(5), 1900–1938. https://doi.org/10.1093/rfs/hhy137

Thakor, A. V. (2020). Fintech and banking: What do we know? Journal of Financial Intermediation, 41, 1–13. https://doi.org/10.1016/j.jfi.2019.100833

Wang, Q., Xiong, X., & Zheng, Z. (2021). Platform characteristics and online Peer-to-Peer Lending: Evidence from China. Finance Research Letters, 38(February), 1–7. https://doi.org/10.1016/j.frl.2020.101511

Zalan, T., & Toufaily, E. (2017). The promise of Fintech in emerging markets: Not as disruptive. Contemporary Economics, 11(4), 415–430.

Zhang, Z., Hu, W., & Chang, T. (2019). Nonlinear effects of P2P lending on bank loans in a Panel Smooth transition regression model. International Review of Economics and Finance, 59(August 2017), 468–473. https://doi.org/10.1016/j.iref.2018.10.010

Zhou, J., Li, W., Wang, J., Ding, S., & Xia, C. (2019). Default prediction in P2P lending from high-dimensional data based on machine learning. Physica A: Statistical Mechanics and Its Applications, 534, 1–11. https://doi.org/10.1016/j.physa.2019.122370