Lan Thi Phuong Nguyen

Federated risk management in the context of Peer-to-Peer (P2P) lending should be a collaborative approach with multiple autonomous entities (i.e. agent systems) working together to assess, monitor, and mitigate risks. Orchestration of these agents is crucial in facilitating risk evaluation, surveillance, and mitigation tactics. By employing Multi-Agent Systems (MAS), the orchestration of risk, regulatory compliance, and stakeholders' interests are better protected. The framework of federated risk management in P2P lending aims to address challenges and risks inherent in decentralized platforms. In recent years, the P2P lending industry has experienced significant growth, attracting both borrowers and investors seeking an alternative financial system. However, this growth has exposed the industry to various risks, including credit risk, fraud, and information asymmetry. As a result, the need for a robust risk management framework has become increasingly critical. In this paper, we delve into the role of intelligent agents and their protocol for collaborative dynamics that uses the portfolio's return (Rp) and the risk-free rate (Rf), divided by the standard deviation of the portfolio's excess return (σp) for various investment portfolios. Our framework allows MAS to analyze data from diverse sources, default rates, payback history, and portfolio risks to propose adaptive strategies for risk mitigation. Doi: 10.28991/HIJ-2024-05-04-06 Full Text: PDF

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

In the context of Peer-to-Peer (P2P) lending, risk controls are required, and they usually refer to a set of procedures and operations that aim to protect the integrity of data, particularly for accurate financial representation within the platform. Risk control procedures need to be in place to ensure accountability and fairness in risk and return trade-offs on federated platforms. This will foster trust among participants, especially when multiple fraud cases in the past, such as Enron, Madoff Investment Securities, and WorldCom, have accentuated the importance of a robust internal control mechanism in maintaining the credibility of the financial ecosystem. Stakeholders in the P2P lending industry are becoming increasingly concerned about the issue of trust, necessitating a re-evaluation of internal control frameworks to uphold objectivity and reliability. With the growth of the P2P lending industry as an alternative lending and borrowing platform and the requirement of an autonomous P2P lending platform, complexity arises, and autonomous entities (i.e., MAS) working together to assess, monitor, and mitigate risks is the only solution for such complexities. The orchestration of MAS plays a pivotal role in facilitating and mitigating risks. This study aims to provide a process methodology for fostering collaborative dynamics within the P2P lending domain. A state diagram approach is presented, where state orders (SO), lending approvals, risk graphs, risk ordering relations, and risk bands (RB) are introduced for MAS to assume certain roles or tasks. For each task, controls for the segregation of duties are presented as well. Given the absence of proper autonomous systems for decision-making, robust internal control methods are necessary for controls to execute federated trust on lending platforms. Our approach will significantly improve investors’ confidence meant to achieve this goal. Doi: 10.28991/ESJ-2024-08-04-024 Full Text: PDF

Background: Since 2016, the Securities Commission (SC) in Malaysia has given licenses to only eleven P2P lending platforms. Such lending platforms are expected to disrupt the lending services of traditional lenders in the coming years. However, being still in their infant stages, it is essential to know the extent to which such platforms are made known to potential investors out there. This study aims to examine the awareness level of the eleven P2P lending platforms among Malaysian adults. The study also explores if past investment experience and financial knowledge would influence such awareness from Malaysian adults. Methods: A sample of 335 Malaysian individuals was used for this study. An online questionnaire was designed with three main parts: demographic, financial literacy, and P2P lending awareness. Using IBM SPSS Statistics 26, frequency, descriptive, normality, Pearson coefficients and multiple regression analyses were carried out. Results: Although seven out of ten respondents have good knowledge in three areas of finance: compounding rate, inflation and diversification, only 14.33% had a good and excellent awareness level of P2P lending. Thus, one would expect lesser awareness about P2P lending among Malaysian adults whose financial literacy is poor or zero. Test results from multiple regression analysis suggest that past lending experiences positively affect the awareness of P2P lending in Malaysia, but not the financial literacy. Conclusions: The awareness about P2P lending among Malaysian adults is too low, despite their high level of education and financial literacy. No investing experience and not knowing any existing P2P lending in the country may be the reason for this low awareness. Therefore, for P2P lending to thrive in Malaysia, the eleven P2P lending platforms need to be promoted aggressively in various social media outlets.

Mobile banking has the benefits of internet banking, in which the customer can access bank services over an internet connection anytime and anywhere. Millennials in Malaysia’s business environment are an enormous segment of the Malaysian population, and they are moving to take their places in the middle and high levels of their companies’ managerial governance pyramid these days and in the near future. This study examines the question, “What are the main factors that may influence mobile banking use (MBU) and the intention to use mobile banking (IU) among millenial consumers in Malaysia?”. The determining factors of UTAUT, performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), hedonic motivation (HM), price value (PV), habit (Ha), perceived risk (PDR), and interface design quality (IDQ) were tested in this study. Method: SPSS and PLS-SEM are employed on a collected sample of 504 respondents of Millennials in Malaysia using a well-defined questionnaire to carry out all statistical analyses of this study. Result: The study model can explain 55.3% of the variance of mobile banking use (MBU) and 60.3% of the intention to use mobile banking (IU). In this study, all the relations of the model are significant, except the relation between price value (PV) and the intention to use mobile banking. For both IU and MBU in the model, the factor “Interface design quality” (IDQ) has the highest impact. In contrast, the factor “Perceived Risk” (PDR) has the lowest impact. The findings of this study extend the knowledge on mobile banking as an approach of financial technology implementation, from which mobile banking providers and interface designers can provide new potential solutions to expand the usage of mobile banking services in Malaysia. This study proposed a modified model with eleven variables. While the designed model was evaluated successfully and explained 55% of actual use and 60% of intentional use, the remaining portion (45% for actual use and 40% for intended usage) exposes yet other factors that are still unrevealed. Therefore, further studies are required to assess the design in various other financial sectors, and further studies are invited to conduct qualitative research to reveal other variables for a better understanding of the intention and actual use of mobile banking.

Background - With the recent evolution of Financial Technology (FinTech), 11 peers to peer (P2P) lending platforms have been regulated by the Securities Commission in Malaysia since 2016. P2P lending platforms offer new investment opportunities to individual investors to earn higher rates on return than what traditional lenders usually provide. However, individual investors may face higher potential risks of default from their borrowers. Therefore, individual investors need to understand the potential exposure to such P2P lending platforms to make an effective investment decision. This study aims to explore the potential risk exposures that individual investors may experience at Malaysia's licensed P2P lending platforms. Methods - Based on data collected manually from nine P2P lending platforms over five months, relationships between interest rates and various risk classifying factors such as credit rating, industry, business stage, loan purpose, and loan duration are examined. Results- This study shows that loans with a similar credit rating and with or without similar loan purpose; and a business stage may offer investors significantly different interest rates. In addition, loans with shorter durations may provide investors with higher interest rates than those with longer durations. Finally, loans issued by companies from the same industry appeared to be charged with similar interest. These findings are valuable to investors to prepare themselves before making their investments at the P2P lending platforms. Conclusion- With first hand-collected data, this study provides an original insight into Malaysia's current P2P lending platforms. Findings obtained for relationships between interest rates and risk classifying factors such as credit rating, industry, business stage, loan purpose and loan duration are valuable to investors of Malaysian P2P lending platforms.

Since the 2008 global financial crisis, many innovations have emerged in the financial sector as investors started to look for alternative methods to eliminate irrational decision-making in wealth management, and Robo-advisors is among those. Nine years after the first launching of Robo-advisors in the U.S. in 2008, the Securities Commission Malaysia has been issuing licenses to seven Robo-advisor platforms. The current COVID-19 outbreak has made this industry more in demand, increasing 763% in registration in 2020. However, much skepticism about Robo advisors’ ability and reliability in providing a similar quality or better advisory service compared to human-financial advisors. Therefore, this study examines the factors influencing the acceptance of Robo-advisors in wealth management in Malaysia. Adopting some factors from various established technology acceptance models, an online survey with 122 respondents was conducted using convenience sampling. Findings show that Relative Advantage, Effort Expectancy, and Social Influence significantly positive influence the Malaysian Behavioral Intention to Accept Robo-Advisors. On the contrary, there is no significant relationship between Perceived Risk and Malaysian Behavioral Intention to Accept Robo-Advisors. The study provides a positive insight into factors influencing the acceptance of Robo-Advisors in Malaysia.