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Building trust in robo-advisory: technology, firm-specific and system trust

Xue Cao et al.

Qualitative Research in Financial Markets2025https://doi.org/10.1108/qrfm-02-2024-0033article
AJG 1ABDC B
Weight
0.50

What the paper says

Purpose This study sits at the intersection of financial planning and FinTech, focusing on robo-advisory, an affordable and accessible digital financial advisory service. Individuals’ lack of trust has resulted in low adoption of robo-advice. This study aims to understand the psychological process of how individuals build trust in robo-advice, helping them engage with it more effectively and access affordable financial advice. Design/methodology/approach Using a trust transfer theory framework and 15 semi-structured interviews, this study identifies the sources people rely on to build trust in robo-advice. Findings The authors highlight four themes – social influence, psychological comfort, safeguarding and compliance and personal capacity – that shape individuals’ trust in robo-advice. In addition to direct trust in robo-advice, firm-specific trust and system trust can also transfer to trust in robo-advice. This study finds that financial literacy and risk tolerance moderate individuals’ trust in robo-advice, while psychological comfort first shapes trust and then drives adoption. The findings suggest that even young, tech-savvy individuals may not fully benefit from robo-advice due to low personal capability. They also prefer a hybrid model, where combining robo-advice with traditional advisory services could offer greater benefits. Originality/value This study details the concept of trust in the robo-advice context into three dimensions: technology trust, firm-specific trust and system trust. Existing research on robo-advice lacks quantitative tests on firm-specific and systemic trust; therefore, this qualitative exploratory study offers foundational theoretical insights.

6 citations

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https://doi.org/https://doi.org/10.1108/qrfm-02-2024-0033

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@article{xue2025,
  title        = {{Building trust in robo-advisory: technology, firm-specific and system trust}},
  author       = {Xue Cao et al.},
  journal      = {Qualitative Research in Financial Markets},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1108/qrfm-02-2024-0033},
}

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Building trust in robo-advisory: technology, firm-specific and system trust

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.44 × 0.4 = 0.18
M · momentum0.65 × 0.15 = 0.10
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.