Determinan Gagal Bayar P2P Lending di Jawa Barat dengan Pendekatan ARDL

Authors

  • Meysa Mariela Faradyas Zahra Universitas Negeri Surabaya
  • Ladi Wajuba Perdini Fisabilillah Universitas Negeri Surabaya

DOI:

https://doi.org/10.26740/independent.v6i1.76372

Keywords:

P2P lending, default risk , unemployment,, inflation, ARDL

Abstract

This study aims to analyze the determinants of peer-to-peer (P2P) lending default in West Java Province using outstanding loan, number of borrowers, unemployment rate, and inflation as explanatory variables. The study employs the Autoregressive Distributed Lag (ARDL) approach to examine both short-run and long-run relationships among the variables. The results indicate that in the long run, outstanding loans, unemployment, and inflation have a positive and significant effect on default, while the number of borrowers has a negative and significant effect. In the short run, the dynamics of default show a pattern that is relatively consistent with the long-run relationship. These findings suggest that the default risk of P2P lending is influenced by a combination of credit expansion and regional macroeconomic conditions. Therefore, strengthening risk management and enhancing supervision over loan growth are essential to maintain the stability of digital financing.

Downloads

Download data is not yet available.

References

Ahmed, S., Majeed, M. E., Thalassinos, E., & Thalassinos, Y. (2021). The Impact of Bank Specific and Macro-Economic Factors on Non-Performing Loans in the Banking Sector: Evidence from an Emerging Economy. Journal of Risk and Financial Management, 14(5). https://doi.org/10.3390/jrfm14050217

Akerlof. (1970). The Market for “Lemons” : Quality Uncertainty and the Market Mechanism (pp. 488–500). QuarterlyJournal of Economics.

Akhter, N. (2023). Determinants of commercial bank’s non-performing loans in Bangladesh: An empirical evidence. Cogent Economics and Finance, 11(1). https://doi.org/10.1080/23322039.2023.2194128

Albashayreh, E. (2024). Factors Influencing Non-Performing Loans in Jordanian Banks: A Dual Macro-Micro Perspective. Pakistan Journal of Life and Social Sciences, 22(2), 10759–10777. https://doi.org/10.57239/PJLSS-2024-22.2.00813

Aprita. (2021). Peranan Peer to Peer Lending dalam Menyalurkan Pendanaan pada Usaha Kecil dan Menengah. Jurnal Hukum Samudra Keadilan, 16(1), 37–61. https://doi.org/https://doi.org/10.33059/jhsk.v16i1.3407

Avgeri, E., & Psillaki, M. (2024). Factors determining default in P2P lending. Journal of Economic Studies, 51 (4), 823–840. https://doi.org/10.1108/JES-07-2023-0376

Bernanke, B., & Gertler, M. (1986). Agency Costs, Collateral, and Business Fluctuations. American Economic Review, 70, 14–31. https://doi.org/10.3386/w2015

Fisabilillah, L. W. P., Seno Aji, T., S.P, P., & Hanifa, N. (2024). Analysis of the Effect of Financial Literacy On the Use of Financial Technology in the Society 5.0 Era. KnE Social Sciences, 2024, 80–90. https://doi.org/10.18502/kss.v9i4.15060

Frost, J., Stability, F., Gambacorta, L., Settelments, I., Zbinden, P., Libre, M., Frost, J., Gambacorta, L., Huang, Y., & Shin, H. S. (2019). BigTech and the Changing Structure of Financial Intermediation. Economic Policy, 34, 761–799.

Hartanto, A. D., & Setijaningsih, H. T. (2023). Determinan Probability of Default Dalam Perhitungan Expected Credit Loss Perbankan. Akurasi : Jurnal Studi Akuntansi Dan Keuangan, 6(1), 157–176. https://doi.org/10.29303/akurasi.v6i1.329

Huijbers, T. (2019). The Effect of Macroeconomic Factors on Default Risk in Online P2P Lending: Evidence From A European Platform.

Hull, J. C. (2012). Risk Management and Financial Institutions,+ Web Site. John Wiley & Sons, 733, 1–31.

Jagtiani, J., & Lemieux, C. (2019). The Roles of Alternative Data and Machine Learning in Fintech Lending : Evidence from the LendingClub. Financial Management, 48, 1009–1029. https://doi.org/https://doi.org/10.21799/frbp.wp.2018.15

Kusuma, E. C., & Haryanto, A. M. (2016). Analisis pengaruh variabel kinerja bank (CAR, ROA, BOPO dan LDR), serta pertumbuhan kredit dan kualitas kredit terhadap Non Performing Loan (NPL). Diponegoro Journal of Management, 5(2015), 1–13.

Liu, Y., & Mona, K. (2025). Characteristics of High-Risk Defaulters: An Empirical Study on the Bondora P2P Lending Platform. Proceedings of the Annual Hawaii International Conference on System Sciences, 6868–6875. https://doi.org/10.24251/hicss.2025.820

Markowitz. (1991). Foundations of Portfolio Theory. Journal of Finance, 46(2), 469–477.

Merton, R. C. (1974). On the Pricing of Corporate Debt: the Risk Structure of Interest Rates. The Journal of Finance, 29(2), 449–470. https://doi.org/10.1111/j.1540-6261.1974.tb03058.x

Nazir, M. R., Tan, Y., & Nazir, M. I. (2021). Financial innovation and economic growth: Empirical evidence from China, India and Pakistan. International Journal of Finance and Economics, 26(4), 6036–6059. https://doi.org/10.1002/ijfe.2107

Nigmonov, A., Shams, S., & Alam, K. (2022). Macroeconomic determinants of loan defaults: Evidence from the U.S. peer-to-peer lending market. Research in International Business and Finance, 59(August 2021), 101516. https://doi.org/10.1016/j.ribaf.2021.101516

OJK, (Otoritas Jasa Keuangan). (2022). Statistik Fintech Lending Desember 2021. Jakarta. https://ojk.go.id/id/kanal/iknb/data-dan-statistik/Fintech/default.aspx

OJK, (Otoritas Jasa Keuangan). (2024). Peraturan Otoritas Jasa Keuangan Nomor 40 Tahun 2024 Tentang Layanan Pendanaan Bersama Berbasis Teknologi Informasi.

Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289–326. https://doi.org/https://doi.org/10.1002/jae.616

Pratama, K., Sulistomo, A., Lestari, H. S., & Margaretha, F. (2025). Banking Health Indicators and Their Impact on Credit Risk in the Indonesian Banking Sector. Indonesian Interdisciplinary Journal of Sharia Economics (IIJSE), 8(2), 3464–3481. https://doi.org/https://doi.org/10.31538/iijse.v8i2.6316

Putri, D. M. N., & Zakik, Z. (2023). Analisis Pengaruh Indikator Makroekonomi Terhadap Non Performing Loan (NPL) Di Indonesia Tahun 2016-2020. Buletin Ekonomika Pembangunan, 3(2), 267–279. https://doi.org/10.21107/bep.v3i2.18394

Ruhana, N. (2023). Forecasting Analysis of the Development of Fintech Lending Financial Performance in Indonesia. Indonesian Journal of Economics and Management, 4(1), 62–72. https://doi.org/10.35313/ijem.v4i1.5497

Sastrawati, T., & Muchtar, S. (2024). Pengaruh Macroeconomi dan Bank Specific terhadap Non- Performing Loans pada Bank KBMI 3 yang Terdaftar di Bursa Efek Indonesia. El-Mal: Jurnal Kajian Ekonomi & Bisnis Islam, 5(4), 2469–2476. https://doi.org/10.47467/elmal.v5i4.1096

Suryono, R. R., Purwandari, B., & Budi, I. (2019). Peer to peer (P2P) lending problems and potential solutions: A systematic literature review. Procedia Computer Science, 161, 204–214. https://doi.org/10.1016/j.procs.2019.11.116

Theong, J. M., Farid, A., & Fei, S. (2018). Household Indebtedness : How global and Domestic Macro-economic Factors Influence Credit Card Debt Default in. 10(3), 37–56.

Viet, H. P., Do, V. B., Phan, N. H., Lan, P. D. T., & Ngoc, D. V. (2023). Determinants Influencing Non-Performing Loan Ratio of Joint Stock Commercial Banks in Vietnam. Journal Of Organizational Behavior Research, 8(1), 214–230. https://doi.org/10.51847/MLW0q35dLC

Zawadzki, A. (2023). Macroeconomic Determinants of Credit Risk on the Example of Non-performing Loans. Central European Economic Journal, 10(57), 275–286. https://doi.org/10.2478/ceej-2023-0016

Published

19-04-2026

How to Cite

Meysa Mariela Faradyas Zahra, & Ladi Wajuba Perdini Fisabilillah. (2026). Determinan Gagal Bayar P2P Lending di Jawa Barat dengan Pendekatan ARDL . Independent: Journal of Economics, 6(1), 276–298. https://doi.org/10.26740/independent.v6i1.76372

Issue

Section

Articles
Abstract views: 36 , PDF Downloads: 15