Antecedents and Boundary Conditions of Trust in Algorithmic Financial Advisory Systems: A Structural Examination within Nepal’s Retail Investment Ecosystem

Abstract

This study explores how retail investors in Nepal build trust in Financial Robo-Advisory (FRA) services and how that trust affects their willingness to use such platforms. Using data collected from 520 retail investors and analyzed through PLS-SEM, the study found that trust is strongly shaped by factors such as personal trust tendency, perceived reliability and competence of robo-advisors, social influence, enjoyment in using digital platforms, supporting infrastructure, price value, and ease of access. However, effort expectancy showed a negative effect, suggesting that many investors in Nepal still perceive FinTech systems as difficult to understand due to limited digital literacy and low exposure to advanced financial technologies. The findings further reveal that younger investors are more confident and willing to adopt robo-advisory services than older investors, who generally prefer traditional financial consultation methods. By extending the UTAUT framework with trust-related dimensions, the study offers useful insight into digital financial adoption in emerging economies. The results highlight the need for financial institutions and policymakers to improve digital awareness, simplify platform design, strengthen internet accessibility, and ensure transparent and secure financial services to encourage wider adoption of robo-advisory systems.