MUMBAI, India, Jan. 2 -- Intellectual Property India has published a patent application (202541124113 A) filed by Keshav Memorial Institute Of Technology, Hyderabad, Telangana, on Dec. 9, 2025, for 'deep learning based health insurance risk prediction system with intelligent policy recommendation and interactive customer behavior analytics for enterprise insurance management.'
Inventor(s) include Mr. Aggadi Gnanesh; Mr. K Rajesh Kumar; Mr. Para Upendar; Mr. Gunturi Sai Saatvik; Ms. Seelam Akshaya; Mr. Aitha Bavesha Prasad; and Kuthuru Rajkumar.
The application for the patent was published on Jan. 2, under issue no. 01/2026.
According to the abstract released by the Intellectual Property India: "The Health Insurance Risk Prediction System is an advanced AI-powered platform designed to revolutionize insurance customer assessment and policy management through sophisticated deep learning techniques. The system automates the classification of customers as "prominent" (eligible) or "non-prominent" (ineligible) for insurance coverage, addressing critical deficiencies in traditional manual underwriting processes. The core innovation features a residual deep neural network architecture trained on comprehensive health and demographic datasets, achieving 97% accuracy in risk classification compared to 70-80% for conventional methods. This enables insurance companies to make rapid, data-driven decisions within 3 seconds-previously requiring hours or days. The system provides intelligent policy recommendations through a matching algorithm that correlates customer risk profiles with appropriate insurance products, delivering transparent explanations for each recommendation. The dynamic premium calculator generates personalized insurance costs based on individual health factors, lifestyle indicators, and behavioral patterns, enabling smart premium suggestions for cost optimization. The platform integrates a 24/7 AI-powered chatbot (GI) providing customer support, policy guidance, and eligibility clarification, enhancing user engagement and satisfaction. Interactive analytics dashboards deliver real-time visual insights into customer risk distributions, behavioral trends, and policy performance-enabling data-driven business decisions. Deployed on a modern MERN stack architecture (MongoDB, Express.js, React.js, Node.js), the system achieves 99.9% uptime, supports 1000+ concurrent users, and implements enterprise-grade security with HTTPS/TLS encryption, JWT authentication, role-based access control, and GDPR compliance. By automating risk assessment, enabling personalized recommendations, and providing comprehensive analytics, the Health Insurance Risk Prediction System transforms insurance operations, minimizes claims losses, accelerates policy issuance, and significantly improves customer satisfaction."
Disclaimer: Curated by HT Syndication.
