Factors Influencing the Intention to Use Robo- Advisors: A Hungarian Perspective

Abstract

This study aims to investigate the factors influencing the intention to use robo- advisors, based on an extended Unified Theory of Acceptance and Use of Technology (UTAUT) model, incorporating trust and perceived risk as new elements, alongside Artificial Intelligence attributes. To test our conceptual model, we conducted a survey in Hungary in 2024, with 249 respondents completing our online questionnaire. The model and hypotheses were evaluated using structural equation modeling (SEM). The results indicate that the intention to use robo-advisors is most significantly influenced by performance expectancy, trust, social influence, and facilitating conditions. Among the AI attributes, perceived intelligence stands out, exerting an indirect effect on the intention to use through the aforementioned factors. A limitation of our study is its’ geographical focus on Hungary, restricting the generalizability of the findings to potential Hungarian users. Additionally, we were unable to investigate actual usage due to the currently low service penetration. Understanding the factors that influence the preference for automated investment management solutions over traditional advisors is essential for marketing managers in fintech companies to devise effective client acquisition and retention strategies. The findings highlight the importance of trust, security, and digital literacy. Addressing these factors is vital for maximizing the benefits and mitigating the risks associated with AI in financial services. The originality lies in its integrated examination of perceived intelligence and anthropomorphism within an extended UTAUT model, uncovering their combined effects on the intention to use robo-advisors.