Innovating Insurance Lending in Indian Fintech: A Study of Bimapay’s EMI Model, Business Strategy, and Role in Alternative Credit for Insurance Inclusion

Abstract

This study examines EMI-based insurance lending within India’s fintech ecosystem, focusing on Bimapay Finsure Pvt. Ltd. and its role in improving insurance accessibility through technology-enabled premium financing. Using primary data collected from 41 employees across finance, operations, and technology teams, the research evaluates employee understanding of the EMI model, perceptions of business model sustainability, and attitudes toward AI-driven reconciliation. Statistical analyses – including descriptive analysis, correlation, and regression – reveal that employees generally have positive perceptions of efficiency, accuracy, and the usefulness of AI tools. Correlation results show strong positive relationships between system effectiveness, accuracy, and employee trust in AI (r = .579, p < .001), while regression findings confirm that key variables such as perceived accuracy (VAR00005) significantly predict operational efficiency (p < 0.05). However, certain challenges negatively influence outcomes, such as delays due to manual processes and mismatch-related issues (VAR00007), which showed a significant negative effect (p < 0.05). Descriptive analysis indicates consistent agreement among employees regarding the need for automation and centralized dashboards. Overall, the findings highlight that although Bimapay has adopted several digital tools, gaps remain in reconciliation automation, interdepartmental coordination, and real-time data visibility. The study concludes that enhanced API integration, AI-supported anomaly detection, and unified dashboards are crucial to