Conditional Willingness and Regulatory Assurance Expectations for AI Enabled Financial Services in Bangladesh

Artificial intelligence in financial services raises questions about whether willingness to engage reflects confidence in technology, expectations of consumer protection or confidence attributed to institutional safeguards. These positions are frequently discussed together despite their different meanings. This study examines their distribution and association in a Bangladesh sample with substantial legal education and professional representation. A cross-sectional questionnaire database containing 385 consenting, AI-aware adults was analysed at item level. Five protection-related statements were assessed using endorsement distributions, paired contrasts, joint response patterns and exploratory adjusted regression. Low internal consistency discouraged combining the statements into a reflective trust scale. Clear-protection conditional willingness was endorsed by 87.8%, compared with 67.5% for oversight-related trust, 83.6% for disclosure, 83.6% for redress and 84.2% for accountability-related confidence. The oversight statement was endorsed 20.3 percentage points less often than conditional willingness (bootstrap 95% interval −26.0 to −14.8; Holm-adjusted p < 0.001). Only 53.0% endorsed conditional willingness, oversight-related trust and accountability-related confidence together. None of the four focal adjusted associations with willingness met the Holm-corrected threshold; ordinal and law-student-restricted analyses likewise retained none. The findings distinguish broad approval of protective conditions from a supported individual-level model of willingness. Institution-based trust and procedural justice provide interpretive lenses, while the measures do not establish current provider trust, actual financial-service use or regulatory effectiveness. Practical implications concern testing understandable disclosures and accessible review arrangements against operational evidence rather than treating favourable survey responses as evidence of implementation.