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When Advice Isn’t Trusted: Privacy, Transparency, and Accountability Risks Driving AI Mistrust and Consumer Resistance in Financial Advisory Services

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  • Pichit Sungkarungsri

    (Technology of Information System Management Division, Faculty of Engineering, Mahidol University, Nakhon Pathom 73170, Thailand)

  • Supaporn Kiattisin

    (Technology of Information System Management Division, Faculty of Engineering, Mahidol University, Nakhon Pathom 73170, Thailand)

Abstract

The application of AI in financial planning services has the potential to enhance universal access to financial services. However, AI still faces common consumer mistrust and resistance, hindering the long-term sustainability of AI-powered financial planning. This research aims to explain why consumers resist AI in financial planning and the mechanisms that lead to this resistance and negative customer behavior. This research developed a conceptual model by integrating the S-O-B-C framework with Innovation Resistance Theory, AI ethical risks, and social influence that influence AI mistrust and intention to resist, which lead to negative outcomes such as negative word-of-mouth and customer disloyalty in the context of digital financial planning services in Thailand. The research collected data from a sample of 420 persons and the data was analyzed using PLS-SEM. The research identified social influence and the risks associated with AI transparency and accountability as primary factors contributing to AI mistrust, whereas privacy risk serves as a more fundamental catalyst for resistance. This resistance contributes to negative word-of-mouth and leads to customer disloyalty. It emphasizes that developing sustainable AI financial advisors must go beyond technically secure design to transparent, accountable, and socially legitimate governance to maintain long-term relationships with customers in the digital financial system.

Suggested Citation

  • Pichit Sungkarungsri & Supaporn Kiattisin, 2026. "When Advice Isn’t Trusted: Privacy, Transparency, and Accountability Risks Driving AI Mistrust and Consumer Resistance in Financial Advisory Services," Sustainability, MDPI, vol. 18(3), pages 1-41, January.
  • Handle: RePEc:gam:jsusta:v:18:y:2026:i:3:p:1354-:d:1851597
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    Cited by:

    1. Ayasal Anthony Auya & Ovivi Audu Jamiu, 2026. "Artificial Intelligence-Driven Credit Management and Financial Performance of Deposit Money Banks (DMBs) In Abuja, Nigeria," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 13(3), pages 1436-1451, March.

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