Exploratory Review: Trust Dynamics in AI-Enabled Retail Financial Investment Service
Ling Ding, Zhao Zhao, Rhonda N. McEwen · 2024
Trust anchors financial markets, which directly contribute to the foundation of global economies, and simultaneously fuel FinTech innovations. AI-driven tools such as Robo-advisors, Equity crowdfunding, and Peer-to-peer lending reshape investment paradigms, but understanding trust within this digital realm remains elusive. This scoping review examines AI trust dynamics within retail financial investments. We locate and dissect thematic constructs, and assess the complex interplay of pivotal variables. While initial insights emphasize trust’s critical role in FinTech’s evolution, they also illuminate the constraints of a universal framework to analyze trust in this context. Despite the popularity of models like TAM and UTAUT, their inherent weaknesses leave important facets unexplored. While qualitative and quantitative methods predominantly inform the current discourse, many studies base their conclusions on niche or self-crafted hypotheses. Through this systematic review, we chart a path for future discussions on AI-driven financial trust, highlighting gaps, and offering new avenues for exploration.