An AI-Based Insurance Assistant Recommendation Framework for Rural Communities

Abstract

Insurance serves as a vital financial safety net for rural communities, safeguarding them against unforeseen agricultural losses, health emergencies, and natural calamities. However, insurance penetration in rural India, particularly in states like Karnataka, remains critically low. This research paper explores the core challenges hindering rural insurance adoption, including low awareness, language barriers, and complex bureaucratic procedures. To address these systemic issues, this paper proposes the framework for a voice-enabled, multilingual Artificial Intelligence (AI) Insurance Assistant. By utilizing Natural Language Processing (NLP) and Machine Learning (ML), the proposed system acts as a virtual agent capable of communicating in regional dialects (such as Kannada), recommending personalized policies, and simplifying the claims process. The research compares India’s current digital insurance landscape with advanced models in foreign countries to highlight the potential for AI integration. The expected outcome of this proposed system is a significant democratization of insurance access, fostering greater financial literacy, and building resilient rural economies.