The influence of Robo-advisory services on Malaysia university student’s investment intention - Tan, Yung Hui; Lim, Jia Eng; Lim, Keh Xin; Zeng, Yi (2025)
The emergence of robo-advisory services has transformed the landscape of investment by offering automated, algorithm-driven financial planning with minimal human intervention. As financial technology (fintech) continues to advance, understanding the behavioral intentions of young investors toward these services is crucial. This study investigates the influence of perceived risk, trust, and perceived ease of use on the intention to adopt roboadvisory services among Malaysian university students. The study adopts the Technology Acceptance Model (TAM) as the theoretical foundation, integrating elements of trust and perceived risk to examine how these factors impact adoption intentions. Data was collected through a structured questionnaire distributed to university students across Malaysia, and a total of 135 valid responses were analyzed using Jamovi statistical software version 2.6.24. Descriptive and inferential analyses, including multiple regression, were employed to determine the relationships among the variables. The findings reveal that both trust and perceived ease of use have significant positive effects on students' intention to use robo-advisory services. Conversely, perceived risk demonstrates a significant negative relationship, indicating that concerns over data security, financial loss, and technological uncertainty remain barriers to adoption. These results highlight the need for fintech developers and financial service providers to focus on building secure, user-friendly platforms that foster trust and address risk concerns, particularly when targeting young, techsavvy investors. This research contributes to the growing body of literature on fintech adoption in emerging markets and offers practical implications for improving the design, communication, and implementation strategies of robo-advisory services in Malaysia. Future research could expand the sample size and explore other demographic groups to enhance generalizability and provide deeper insights into consumer behavior in the digital investment space.