Trust in human–AI collaboration in finance: a bibliometric–systematic literature review
AI Summary: The article presents a multi-level socio-technical framework that addresses trust in human-AI collaboration within the finance sector, identifying six thematic clusters: AI Governance in Finance, Explainable AI (XAI) for Finance, Anthropomorphism in Financial AI Agents, User Interface Design, Robo-Advisors, and Infrastructural Trust Technologies. The analysis reveals that trust is conceptualized through cognitive, procedural, socio-affective, and behavioral lenses across these clusters, with a notable lack of cross-fertilization among them. Methodologically, survey-based structural equation modeling (SEM) is predominant, while five research frontiers are identified, including the need for frameworks translating responsible AI principles into practice and the development of standardized metrics for XAI. The findings highlight a consistent multi-level pattern in how trust is shaped in this context, emphasizing the importance of integrating various perspectives and methodologies in future research.