Religious and Ethical Dimensions of Trust in AI-Enabled Digital Lending Platforms: A Qualitative Study in Emerging Markets

Abstract

AI-enabled digital lending can expand credit access for small businesses excluded by traditional banks, yet adoption depends on whether owners view opaque platforms as competent, fair, ethically responsible, and consistent with religiously informed expectations. Accordingly, this study examines the religious and ethical dimensions of trust in AI-enabled digital lending platforms across emerging markets. This study examines the process of learning that judgment. It employs a secondary qualitative design, which synthesizes the reported findings of 17 primary empirical studies published between 2021 and 2025. The evidence includes small business owners, borrowers, fintech users, and lending stakeholders in emerging market contexts such as Pakistan, Indonesia, India, Peru, Thailand, and Kenya. Three themes were identified. To start with, the proprietors start with risk-averse and value-driven tests, where velocity and availability excuse experimentation, though they fail to build long-term credibility. Second, predictability, intelligibility, procedural fairness, and clear data boundaries were used to measure trust. Third, trust is institutional/relational when recourse, reputation, regulation, peer testimony, human support, and a lower rate of consequences in the case of a failure lower the cost of doing business. Synthesis posits that trust is situational and temporary in nature. The use can be triggered by convenience, but further use is conditional upon the reaction of the platform during rejection, difficulty in making repayments, data issues, or grievance. This study adds a process explanation of trust calibration and provides useful policy implications for platform design and regulation.