This project develops an integrated framework for satellite risk assessment and insurance premium estimation using data-driven analytical methods. The research addresses the growing complexity of modern satellite missions and emerging space technologies, where conventional risk evaluation approaches are often fragmented, manual, and difficult to scale—especially for missions with limited historical reliability data. The framework combines orbital data, telemetry, mission characteristics, and operational risk indicators into a unified analytical architecture capable of assessing both pre-launch and in-orbit risks. These factors are aggregated into an overall mission risk score, which is subsequently translated into monetary estimates for insurance premium evaluation. A key component of the project is the development of an automated workflow and interactive dashboard that enables real-time visualization of risk metrics, premium estimates, scenario comparisons, and detailed risk breakdowns. By integrating multiple data sources into a centralized system, the framework aims to improve consistency, reduce processing time, minimize human error, and enhance scalability in satellite risk evaluation and space insurance analytics. The project contributes toward next-generation decision-support systems for satellite mission planning, underwriting, and operational risk management in the evolving space economy. Open to collaborations and potential co-founder discussions for MVP development in space insurance analytics and satellite risk assessment.
Parinay Joshi (Thu,) studied this question.