<p>This study examines how trust-related signals are expressed and how they relate to continued engagement, as expressed in reviews, on digital lending platforms, using user-generated content from mobile app marketplaces. Arabic-language reviews from Google Play and the Apple App Store were collected, cleaned, and analyzed using a multi-stage analytics pipeline that combined exploratory text mining, sentiment analysis, topic modeling, construct mapping, and confirmatory modeling. Drawing on an extended UTAUT2 framework, the study operationalizes review-level indicators for performance expectancy, effort expectancy, hedonic motivation, price value, perceived risk, Sharia compliance, emotional assurance, user trust, and continued engagement. The findings show that performance expectancy and effort expectancy are important positive correlates of trust, while perceived risk is negatively associated with trust. The results further show that Sharia compliance and emotional assurance appear as context-specific trust-related signals in digital lending environments. User trust is positively associated with continued engagement expressed in reviews. However, the explanatory power of the engagement models is modest, suggesting that engagement-related expressions in app reviews are influenced by additional factors not captured by the present framework. The study contributes to marketing analytics and fintech research by demonstrating how app review analytics can transform unstructured user feedback into theory-grounded insights into trust and engagement. It also offers practical implications for digital lenders seeking to improve transparency, reassurance, service design, and governance communication in high-stakes financial service settings.</p>