This study explores the quality of service in Indian digital banking apps through a detailed analysis of user-generated reviews, leveraging text-mining techniques for comprehensive insight. This study uses topic modelling and latent Dirichlet allocation (LDA) to segregate and understand both positive and negative reviews by collecting and examining reviews from users of the top three digital banking apps available on Google Play Store. The analysis reveals that positive reviews predominantly identify User Experience, Efficiency, Functionality, and Reliability, whereas negative reviews identify customer support, timeliness, design, and responsiveness. Although the study provides valuable perspectives on service quality, it acknowledges its limitations, including its sole reliance on publicly available reviews which may not capture all customer experiences and the lack of demographic data that could enrich the understanding of how different user groups perceive service quality. Despite these limitations, the findings offer practical insights for banking managers and policymakers in India, highlighting critical areas for service improvement and illustrating the potential of text mining as a tool to enhance digital banking services. This study uniquely contributes to the understanding of digital banking service quality in India by presenting a two-pronged analysis of user feedback, making a significant addition to the literature on digital banking services.