1. Home
  2. Vol 8, No 6 (2024)
  3. Muthaiyah

Federated Risk-Based Access Control Model for P2P Lending Platforms: A Multi-Agent Systems (MAS) Approach

Saravanan Muthaiyah, Lan Thi Phuong Nguyen, Yap Voon Choong, Thein Oak Kyaw Zaw

Abstract


This study addresses the inherent risk management challenges in decentralized finance, particularly for peer-to-peer (P2P) lending platforms. We propose a novel framework that leverages a Multi-Agent System (MAS) to establish a collaborative network encompassing loan originators, investors, regulators, and service providers. This distributed approach facilitates federated risk management, where risk assessment and mitigation responsibilities are shared across these entities. The MAS employs a comprehensive nine-factor assessment (detailed in Table 5) to evaluate industry risk profiles, considering industry environment, competition, and internal capabilities. This data is further visualized using a color matrix (Tables 5 & 6) and utilized alongside state diagrams (Figure 2) to depict the workflow and manage tasks within the P2P lending process. Additionally, the MAS informs a novel Federated Risk-Based Access Control (FRkBAC) system that tailors access permissions (lending origination, disbursement, etc.) based on dynamic risk assessments of industry trends and individual borrower profiles. This data-driven approach fosters trust within the P2P ecosystem and represents a significant advancement in decentralized finance risk management compared to traditional methods.

 

Doi: 10.28991/ESJ-2024-08-06-05

Full Text: PDF


Keywords


P2P Lending; Multi-Agent Systems (MAS); Federated Risk Based Access Control (FRkBAC).

References


Alfian, H. (2020). What You Need To Know About P2P Lending In Malaysia. iMoney Learning Centre, Kuala Lumpur, Malaysia. Available online: https://www.imoney.my/articles/p2p-lending-guide (accessed on November 2024).

Liu, Q., Zou, L., Yang, X., & Tang, J. (2019). Survival or die: a survival analysis on peer-to-peer lending platforms in China. Accounting and Finance, 59(S2), 2105–2131. doi:10.1111/acfi.12513.

Bloomberg News. (2018). How China’s Peer-to-Peer Lending Crash Is Destroying Lives? Available online: https://www.bloomberg.com/news/articles/2018-10-02/peer-to-peer-lending-crash-in-china-leads-to-suicide-and-protest (accessed on November 2024).

Zhe, K. S. K. (2019). P2P Financing Industry Growing. The Edge Communications, Selangor, Malaysia. Available online: https://www.theedgemarkets.com/article/cover-story-p2p-financing-industry-growing (accessed on November 2024).

Gonzalez, L. (2020). Blockchain, herding and trust in peer-to-peer lending. Managerial Finance, 46(6), 815–831. doi:10.1108/MF-09-2018-0423.

Zhang, D., Xu, L., & Wang, C. (2024). The Impact of P2P Platforms on Traditional Intermediaries. Research in Business Applications, 10(1), 12–28.

Khan, S., Shah, M., & Younas, A. (2023). Building Trust in P2P Platforms: A Reputation Management Framework. Journal of Electronic Commerce Research, 14(4), 521–538.

Rosavina, M., Rahadi, R. A., Kitri, M. L., Nuraeni, S., & Mayangsari, L. (2019). P2P lending adoption by SMEs in Indonesia. Qualitative Research in Financial Markets, 11(2), 260–279. doi:10.1108/QRFM-09-2018-0103.

Thakor, R. T., & Merton, R. C. (2018). Trust in Lending. 9th Miami Behavioral Finance Conference 2018, MIT Sloan Research Paper No. 5524-18. doi:10.2139/ssrn.3201689

The World Bank. (2022). World Bank SME Finance: Development News, Research, and Data. World Bank, Washington, D.C., United States. Available online. https://www.worldbank.org/en/topic/smefinance (accessed on November 2024).

Wang, Q., Su, Z., & Chen, X. (2021). Information disclosure and the default risk of online peer-to-peer lending platform. Finance Research Letters, 38, 101509. doi:10.1016/j.frl.2020.101509.

Galloway, I. (2009). Peer-to-Peer Lending and Community Development Finance. Community Development Investment Center Working Paper, 21(3), 20.

Nguyen, L. T. P., Muthaiyah, S., Sy, M. O., & Kalabeke, W. (2022). P2P Lending platforms in Malaysia: the awareness among Malaysian adults. F1000Research, 10, 1096. doi:10.12688/f1000research.73401.2.

Rabbani, M. R., Bashar, A., Hawaldar, I. T., Shaik, M., & Selim, M. (2022). What Do We Know about Crowdfunding and P2P Lending Research? A Bibliometric Review and Meta-Analysis. Journal of Risk and Financial Management, 15(10), 451. doi:10.3390/jrfm15100451.

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. doi:10.1016/j.dss.2016.06.014.

Xia, Y., Liu, C., & Liu, N. (2017). Cost-sensitive boosted tree for loan evaluation in peer-to-peer lending. Electronic Commerce Research and Applications, 24, 30–49. doi:10.1016/j.elerap.2017.06.004.

Banerjee, A., Srinivasan, S., & Pontellini, J. (2023). Decentralized Finance (DeFi) and the Future of P2P Payments. McKinsey Quarterly, 1–10.

Zreik, M., & Iqbal, B. A. (2025). Navigating the Global Fintech Regulatory Landscape: Balancing Innovation and Protection. Examining Global Regulations during the Rise of Fintech, IGI Global, 71-102. doi:10.4018/979-8-3693-3803-2.ch004.

Oh, E. Y., & Rosenkranz, P. (2022). Determinants of peer-to-peer lending expansion: The roles of financial development and financial literacy. The Journal of FinTech, 2(01n02), 2250001. doi:10.1142/S2705109922500018.

Osborn, S., Sandhu, R., & Munawer, Q. (2000). Configuring Role-Based Access Control to Enforce Mandatory and Discretionary Access Control Policies. ACM Transactions on Information and System Security, 3(2), 85–106. doi:10.1145/354876.354878.

Muthaiyah, S., Anbananthen, K. S. M., & Phuong Lan, N. T. (2021). Orchestration of autonomous trusted third-party banking. F1000Research, 10, 899. doi:10.12688/f1000research.72987.1.

Muthaiyah, S. (2006). Propagation and delegation of rights in access controls and risk assessment techniques. Web Services Security and E-Business, 328–337. doi:10.4018/978-1-59904-168-1.ch018.

Nissanke, N., & Dammag, H. (2000). Risk ordering of states in safecharts. Lecture Notes in Computer Science, including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, Vol. 1943, 395–405. doi:10.1007/3-540-40891-6_34.

Kadir, S. U. S. A., & Tunggal, N. Z. (2015). The impact of macroeconomic variables toward agricultural productivity in Malaysia. South East Asia Journal of Contemporary Business, Economics and Law, 8(3), 21-27.

Halim, F. A., Malim, M. R., Derasit, Z., Rani, R. M., & Rashid, S. S. (2017). The impact of macroeconomic variables on SMEs in Malaysia. Journal of Physics: Conference Series, 890(1), 012138. doi:10.1088/1742-6596/890/1/012138.


Full Text: PDF

DOI: 10.28991/ESJ-2024-08-06-05

Refbacks

  • There are currently no refbacks.