Determining Factors of Peer-to-Peer (P2P) Lending Avoidance: Empirical Evidence from Indonesia

Syaiful Ali, Billy Simboh, Ulfa Rahmawati
(Submitted 31 August 2021)
(Published 8 February 2023)


P2P lending offers loans to the public with easy processes and terms. However, the level of P2P lending disbursements is still lower than that of the banks. In addition, a comparison of the number of users of P2P lenders and the productive age population of Indonesia shows that there are still many people who do not use P2P lending. This paper examines the factors that make Indonesians avoid P2P lending. This study used an online survey approach for its data collection and structural equation modeling (SEM) to analyze the data from 499 responses. The study found that the perceived threat from P2P lending is influenced by its perceived severity, perceived susceptibility, and risk tolerance. This perceived threat and social influences cause people’s avoidance motivation. This study contributes to the fintech literature by providing empirical evidence on the avoidance of P2P lending from the borrowers’ perspectives using the TTAT model. Other implications are an input for regulators/governments to enforce the rules for user protection and input for the P2P lending service providers to provide educational programs regarding the use of P2P lending.


fintech, P2P lending, TTAT, SEM, multi-group analysis, Indonesia

Full Text: PDF

DOI: 10.22146/gamaijb.68805


Abu Daqar, M., Constantinovits, M., Arqawi, S. and Daragmeh, A., 2021. The role of Fin- tech in predicting the spread of COVID-19. Banks and Bank Systems, 16(1), pp.1­16.

Ajzen, I., 1985. From Intentions to Actions: A Theory of Planned Behavior. In: J. Kuhl and J. Beckmann, eds. Action Control. [online] Berlin, Heidelberg: Springer Berlin Heidelberg.pp.11-39.

Ajzen, I., 1991. The theory of planned behavior. Organizational Behavior and Human Decision Processes, [online] 50(2), pp.179-211. 5978(91)90020-T.

Ajzen, I. and Fishbein, M., 1980. Understanding attitudes and predicting social behavior. Pbk. Ed. Englewood Cliffs, N.J.: Prentice-Hall.

Alomar, N., Alsaleh, M. and Alarifi, A., 2019. Uncovering the predictors of unsafe com­puting behaviors in online crowdsourcing contexts. Computers & Security, [on­line] 85, pp.300-312.

Arachchilage, N.A.G. and Love, S., 2014. Security awareness of computer users: A phish­ing threat avoidance perspective. Computers in Human Behavior, [online] 38, pp.304-312.

Aziz, A. and Naima, U., 2021. Rethinking digital financial inclusion: Evidence from Bangladesh. Technology in Society, 64, p.101509. soc.2020.101509.

Bain & Company, Google, and Temasek, 2019. Fulfilling Its Promise The Future of South­east Asia’s Digital Financial Services.

Bandura, A., 1982. Self-efficacy mechanism in human agency. American Psychologist, [online] 37(2), pp.122-147.

Bank Indonesia, 2021. Joint Statement OJK, BANK INDONESIA, RI POLICE, KOMIN- FO and Kemenkop UKM In Eradication of Illegal P2P Lending. [online] Avail­able at: < sp_2321621.aspx> [Accessed 24 Aug. 2021].

Barsky, R.B., Juster, F.T., Kimball, M.S. and Shapiro, M.D., 1997. Preference Parameters and Behavioral Heterogeneity: An Experimental Approach in the Health and Re­tirement Study. The Quarterly Journal of Economics, [online] 112(2), pp.537-579.

van Bavel, R., Rodriguez-Priego, N., Vila, J. and Briggs, P., 2019. Using protection motiva­tion theory in the design of nudges to improve online security behavior. Interna­tional Journal of Human-Computer Studies, [online] 123, pp.29-39. https://doi. org/10.1016/j.ijhcs.2018.11.003.

Berger, S.C. and Gleisner, F., 2009. Emergence of Financial Intermediaries in Electron­ic Markets: The Case of Online P2P Lending. Business Research, [online] 2(1), pp.39-65.

Boysen, S., Hewitt, B., Gibbs, D. and McLeod, A., 2019. Off-The-Shelf Artificial Intel­ligence Technologies for Sentiment and Emotion Analysis: A Tutorial on Using IBM Natural Language Processing. Communications of the Association for Infor­mation Systems, [online] pp.95-104.

Browne, K., 2005. Snowball sampling: using social networks to research non-heterosexual women. International Journal of Social Research Methodology, 8(1), pp.47-60.

Burhan, F.A., 2021. Perpetrators of 14 Illegal Borrowing Cases Arrested, Access and Steal Borrower Data. [online] 20 Aug. Available at: < wati/digital/611f39dfc4b29/pelaku-14-kasus-pinjol-ilegal-ditangkap-akses-dan- curi-data-peminjam> [Accessed 24 Aug. 2021].

Carpenter, D., Young, D.K., Barrett, P. and McLeod, A.J., 2019. Refining Technology Threat Avoidance Theory. Communications of the Association for Information Systems, [online] pp.380-407.

Carver, C.S., 2006. Approach, Avoidance, and the Self-Regulation of Affect and Action. Motivation and Emotion, [online] 30(2), pp. 105-110. s11031-006-9044-7.

Carver, C.S. and Scheier, M.F., 1982. Control theory: A useful conceptual framework for personality-social, clinical, and health psychology. Psychological Bulletin, [on­line] 92(1), pp.111-135.

Chen, D. and Han, C., 2012. A Comparative Study of online P2P Lending in the USA and China. The Journal of Internet Banking and Commerce.

Chen, D., Lai, F. and Lin, Z., 2014. A trust model for online peer-to-peer lending: a lender’s perspective. Information Technology and Management, [online] 15(4), pp.239­254.

Chen, D., Lou, H. and Van Slyke, C., 2015. Toward an Understanding of Online Lending Intentions: Evidence from a Survey in China. Communications of the Association for Information Systems, [online] 36.

Chen, D.Q. and Liang, H., 2019. Wishful Thinking and I.T. Threat Avoidance: An Ex­tension to the Technology Threat Avoidance Theory. IEEE Transactions on En­gineering Management, [online] 66(4), pp.552-567. TEM.2018.2835461.

Chen, H. and Li, W., 2017. Mobile device users’ privacy security assurance behavior: A technology threat avoidance perspective. Information & Computer Security, [on­line] 25(3), pp.330-344.

Chen, X., Chong, Z., Giudici, P. and Huang, B., 2020. Networking with Peers: Evidence From a P2P Lending Platform. Asian Development Bank Institute.

Chen, X. (Jack), Chen, Y. and Xiao, P., 2013. The Impact of Sampling and Network Topol­ogy on the Estimation of Social Intercorrelations. Journal of Marketing Research, 50(1), pp.95-110.

Chen, Y. (2013). Domestic online P2P companies mutate into shadow banks - Ali should prevent the systemic risk of scale loans. Oriental Morning Post, June 24.

Chin, W.W., Marcolin, B.L. and Newsted, P.R., 2003. A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and an Electronic-Mail Emotion/Adoption Study. Information Systems Research, 14(2), pp.189-217.

Churchill, G.A., 1979. A Paradigm for Developing Better Measures ofMarketing Constructs. Journal of Marketing Research, 16(1), p.64.

Davis, K., Maddock, R., and Foo, M., 2017. Catching up with Indonesia’s fintech industry. Law and Financial Markets Review, [online] 11(1), pp.33-40. 080/17521440.2017.1336398.

Edwards, J.R., 1992. A Cybernetic Theory of Stress, Coping, and Well-Being in Organiza­tions. Academy of Management Review, [online] 17(2), pp.238-274. https://doi. org/10.5465/amr.1992.4279536.

Eren, B.A., 2021. Determinants of customer satisfaction in chatbot use: evidence from a banking application in Turkey. International Journal of Bank Marketing, 39(2), pp.294-311.

Financial Services Authority, 2016. Financial Services Authority Regulation Number 77 / POJK.01/2016 Concerning Information Technology Based Loaning Services.

Financial Services Authority in Indonesia, 2017. Circular Letter of The Financial Services Authority Number 18 /Seojk.02/2017 Concerning Information Technology Risk Governance and Management in Information Technology Based Loaning Servic­es.

Financial Services Authority in Indonesia, 2019. FAQ Regarding Information Technol­ogy-Based Lending and Borrowing Services - Category of Organizing Com­pany. Available at: < Documents/Pages/FAQ-Terkait-Layanan-Pinjam-Meminjam-Uang-Berbasis-Te- knologi-Informasi---Kategori-Perusahaan-Penyelenggara/> [Accessed 26 Aug. 2021].

Financial Services Authority in Indonesia, 2021a. Fintech Lending Company Licensed and Registered with OJK as of July 27, 2021. Indonesia: Financial Services Author­ity in Indonesia.

Financial Services Authority in Indonesia, 2021b. Indonesian Fintech Lending Statistics June 2021. Indonesia: Financial Services Authority in Indonesia.

Financial Services Authority in Indonesia, 2021c. Press Release: Investment Alert Task Force Strengthens Law Enforcement to Fight Illegal Online Loans. [online] Finan­cial Services Authority in Indonesia. Available at: < ita-dan-kegiatan/siaran-pers/Pages/Satgas-Waspada-Investasi-Perkuat-Penega- kan-Hukum-Berantas-Pinjaman-Online-Ilegal.aspx> [Accessed 24 Aug. 2021].

Galloway, I., 2009. Peer-to-Peer Lending and Community Development Finance. Com­munity Investments, 21(3), pp.19-23.

Goodman, L.A., 1961. Snowball Sampling. The Annals of Mathematical Statistics, 32(1), pp.148-170.

Grable, J.E., 2000. Financial Risk Tolerance and Additional Factors That Affect Risk-Tak­ing in Everyday Money Matters. Journal of Business and Psychology, [online] 14(4), pp.625-630.

Heckathorn, D.D., 2011. Comment: Snowball versus Respondent-Driven Sampling. Sociological Methodology, 41(1), pp.355-366. 111/j.1467- 9531.2011.01244.x.

Herath, T., Chen, R., Wang, J., Banjara, K., Wilbur, J. and Rao, H.R., 2014. Security ser­vices as coping mechanisms: an investigation into user intention to adopt an email authentication service: Security services as coping mechanisms. Informa­tion Systems Journal, [online] 24(1), pp.61-84. 111/j.1365- 2575.2012.00420.x.

Hidajat, T., 2019. Unethical practices peer-to-peer lending in Indonesia. Journal of Fi­nancial Crime, [online] 27(1), pp.274-282. 0028.

Huang, R.H., 2018. Online P2P Lending and Regulatory Responses in China: Opportuni­ties and Challenges. European Business Organization Law Review, [online] 19(1), pp.63-92.

Huang, W, Qian, Y. and Xu, N., 2020. The signaling effects of education in the online lend­ing market: Evidence from China. Economic Modelling, [online] 92, pp.268-276.

Ikhalia, E., Serrano, A., Bell, D. and Louvieris, P., 2019. Online social network securi­ty awareness: mass interpersonal persuasion using a Facebook app. Information Technology & People, [online] 32(5), pp.1276-1300. 06-2018-0278.

Indonesia Fintech Association, 2020. Annual Member Survey 2019/2020. Indonesia Fin- tech Association.

Indonesian Central Bureau of Statistics, 2018. Projection of Indonesian Population 2015­2045. Indonesian Central Statistics Agency.

Janz, N.K. and Becker, M.H., 1984. The Health BeliefModel: A Decade Later. Health Education Quarterly, [online] 11(1), pp.1-47.

Joreskog, K.G. and Wold, H., 1982. The ML and PLS Techniques for Modeling with Latent Variables: Historical and Comparative Aspects. In: Systems Under Indirect Obser­vation: Causality, Structure.

Khan, M.T.I. and Xuan, Y.Y., 2021. Drivers of lending decision in peer-to-peer lending in Malaysia. Review of Behavioral Finance, [online] ahead-of-print(ahead-of-print).

Kotz, S. ed., 1982. Encyclopedia of statistical sciences. A Wiley-Interscience publication. New York, NY: Wiley.

KPMG, 2021. Pulse of Fintech H1’21. [online] Available at: <>.

Lai, F., Li, D. and Hsieh, C.-T., 2012. Fighting identity theft: The coping perspective. Decision Support Systems, 52(2), pp.353-363.

Lee, J.N., Morduch, J., Ravindran, S., Shonchoy, A. and Zaman, H., 2021. Poverty and Mi­gration in the Digital Age: Experimental Evidence on Mobile Banking in Bangla­desh. American Economic Journal: Applied Economics, 13(1), pp.38-71. https://

Li, X., Jiang, X. and Yang, Y., 2021. Learning by P2P bidding. Asia-Pacific Journal of Ac­counting & Economics, [online] pp.1-24. .1879658.

Liang, H. and Xue, Y., 2010. Understanding Security Behaviors in Personal Computer Us­age: A Threat Avoidance Perspective. Journal of the Association for Information Systems, [online] 11(07), pp.394-413.

Liang and Xue, 2009. Avoidance of Information Technology Threats: A Theoretical Per­spective. MIS Quarterly, [online] 33(1), p.71.

Lin, M., Prabhala, N.R. and Viswanathan, S., 2013. Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer- to-Peer Lending. Management Science, [online] 59(1), pp.17-35. https://doi. org/10.1287/mnsc.1120.1560.

Liu, Y., Zhou, Q., Zhao, X., and Wang, Y., 2018. Can Listing Information Indicate Borrower Credit Risk in Online Peer-to-Peer Lending? Emerging Markets Finance and Trade, [online] 54(13), pp.2982-2994.

Lyons, A.C., and Kass-Hanna, J., 2021. Financial Inclusion, Financial Literacy and Eco­nomically Vulnerable Populations in the Middle East and North Africa. Emerging Markets Finance and Trade, 57(9), pp.2699-2738. 6X.2019.1598370.

Nabila, M., 2018. OJK Inaugurates the Presence of AFPI, Special Association for Fintech Lending. [online] Available at: < ing> [Accessed 26 Aug. 2021].

Namvar, E. (2013), “An introduction to peer-to-peer loans as investments”.

Pranata, N. and Farandy, A.R., 2019. Big Data-Based Peer-to-Peer Lending FinTech: Sur­veillance System Through The Utilization of a Google Play Review. Available at: <>.

Qureshi, I. and Compeau, D., 2009. Assessing Between-Group Differences in Information Systems Research: A Comparison of Covariance- and Component-Based SEM. MIS Quarterly, 33(1), p.197.

Respati, A., 2019. As of June 2019, LBH Jakarta Received 4,500 Complaints about Fintech Loans. [online] Available at: <https://money.kom- aduan-soal-pinjaman-fintech> [Accessed September 16. 2020].

Rogers, R.W., 1975. A Protection Motivation Theory ofFear Appeals and Attitude Change1. The Journal of Psychology, [online] 91(1), pp.93-114. 23980.1975.9915803.

Rosavina, M., Rahadi, R.A., Kitri, M.L., Nuraeni, S. and Mayangsari, L., 2019. P2P lending adoption by SMEs in Indonesia. Qualitative Research in Financial Markets, [on­line] 11(2), pp.260-279.

Rosenstock, I.M., 1974. The Health Belief Model and Preventive Health Behav­ior. Health Education Monographs, [online] 2(4), pp.354-386. https://doi. org/10.1177/109019817400200405.

Ryu, H.-S., 2018. What makes users willing or hesitant to use Fintech?: the moderating ef­fect of user type. Industrial Management & Data Systems, [online] 118(3), pp.541­569.

Sangmin Lee, 2017. Evaluation of Mobile Application in User’s Perspective: Case of P2P Lending Apps in FinTech Industry. KSII Transactions on Internet and Information Systems, [online] 11(2).

Schierz, P.G., Schilke, O. and Wirtz, B.W., 2010. Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Re­search and Applications, [online] 9(3), pp.209-216. erap.2009.07.005.

Straub, D.W., 1989. Validating Instruments in MIS Research. MIS Quarterly, 13(2), p.147.

Tao, Q., Dong, Y. and Lin, Z., 2017a. Who can get money? Evidence from the Chinese peer-to-peer lending platform. Information Systems Frontiers, [online] 19(3), pp.425-441.

Tao, Q., Dong, Y. and Lin, Z., 2017b. Who can get money? Evidence from the Chinese peer-to-peer lending platform. Information Systems Frontiers, 19(3), pp.425-441.

The Jakarta Legal Aid Institute, 2020. The Government Should Make A Policy That Pro-

tects Online Loan Users. [online] Available at: < merintah-harus-membuat-kebijakan-yang-mehndungi-pengguna-pinjaman-on- line/> [Accessed 14 Sep. 2020].

Tsai, H.S., Jiang, M., Alhabash, S., LaRose, R., Rifon, N.J. and Cotten, S.R., 2016. Un­derstanding online safety behaviors: A protection motivation theory perspec­tive. Computers & Security, [online] 59, pp. 138-150. cose.2016.02.009.

Venkatesh, Morris, Davis, and Davis, 2003. User Acceptance of Information Technol­ogy: Toward a Unified View. MIS Quarterly, [online] 27(3), p.425. https://doi. org/10.2307/30036540.

Victoria, A.O., 2021. Interest Down Trend, Credit Disbursement Still Minus 2,4% in April. [online] Available at: < tren-bunga-menurun-penyaluran-kredit-masih-minus-2-4-pada-april> [Ac­cessed 24 Aug. 2021].

Vroom, V.H., 1995. Work and motivation. 1. Ed. The Jossey-Bass management series. San Francisco, Calif: Jossey-Bass.

Wang, T., Zhou, L., Mou, Y., and Zhao, J., 2014. Study of country-of-origin image from legitimacy theory perspective: Evidence from the USA and India. Industrial Mar­keting Management, [online] 43(5), pp.769-776. marman.2014.04.003.

Wang, X., Xu, Y.C., Lu, T. and Zhang, C., 2020. Why do borrowers default on online loans? An inquiry of their psychology mechanism. Internet Research, [online] 30(4), pp.1203-1228.

Weinstein, N.D., 2000. Perceived probability, perceived severity, and health-protective be­havior. Health Psychology, [online] 19(1), pp.65-74. 6133.19.1.65.

Wiener, N., 2019. Cybernetics: or, Control and communication in the animal and the ma­chine. Second edition, 2019 reissue ed. Cambridge, MA: The MIT Press.

Xu, W., Zuo, Y., Gao, X. and Yao, M., 2019. The influencing factors of satisfaction and lending intention in online lending investment: an empirical study based on the Chinese market. Accounting & Finance, [online] 59(S2), pp.2045-2071. https://

Yadika, B., 2019. YLKI: Consumer Complaints Regarding Fintech Dominate in Semester I 2019. [online] Available at: <https://www.liputan6. com/bisnis/read/4016800/ylki-aduan-konsumen-terkait-fintech-mendomina- si-di-semester-i-2019> [Accessed September 16. 2020].

Yoon, C. and Kim, H., 2013. Understanding computer security behavioral intention in the workplace: An empirical study of Korean firms. Information Technology & Peo­ple, [online] 26(4), pp.401-419.


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