Regulatory Oversight of AI-Enabled Financial Consumer Services

Abstract

Background: Differences in how institutions address AI finance raise important questions about accountability, administrative consistency, and effective implementation.

Objective: The research compared approaches to AI finance and explored which governance features were most closely associated with outcomes involving consumer protection.

Methods: A mixed-method observational study was conducted across 8 jurisdictions and 16 institutions. Documentary and administrative evidence was coded with a standardized framework and, where applicable, supplemented with stakeholder or practitioner data. Descriptive and multivariable analyses compared implementation patterns and institutional correlates.

Results: The comparative analysis showed uneven implementation of AI finance: 68% of institutions reached the procedural-consistency threshold. Coordination was positively associated with performance, with a 17% improvement on the principal measure, while capacity limitations and ambiguous responsibility dominated the barrier profile.

Conclusion: These findings place institutional capacity at the centre of effective governance relating to AI finance. Accordingly, AI governance in the public sector needs enforceable controls, capable staff, documented accountability, and meaningful human review.

Study design: supervisory practice study.

Publication history: Originally published in print on 15 June 2026, Volume 6, Article 18. Online abstract record added on 16 September 2026. Full-text PDF will be added when the digital galley is ready.