Hybrid vs. Standalone Robo-Advisors: Behavioral and Trust Dynamics in India’s Wealth Management Sector

Abstract

This study examines how emerging financial technologies are reshaping investor behaviour in India’s wealth management sector, with a focus on robo-advisors. Drawing on behavioural finance theory, it compares hybrid models (human and algorithm) with fully automated platforms. Using a mixed-methods approach, original survey data were analysed alongside thematic analysis to evaluate investor trust, satisfaction, and adoption drivers.

Findings reveal a strong preference for hybrid advisory models, driven by the need for personalisation, emotional reassurance, and accountability. While digital literacy enables adoption, algorithmic opacity and concerns over data misuse remain key barriers. Cross-variable analysis indicates that higher digital proficiency correlates with greater openness toward standalone platforms, while lower literacy and financial inexperience favour hybrid systems. Ethical and regulatory expectations particularly regarding transparency and accountability significantly influence adoption decisions.

The study highlights that automation alone cannot ensure investor confidence; trust is coproduced by both human interaction and system transparency. It concludes that the future of robo-advisory in India lies not in replacing human advisors but in redefining their role within hybrid ecosystems that balance efficiency with empathy.