AI-Driven Parametric Insurance Models: The Future of Automated Payouts for Natural Disaster and Climate Risk Management - Lahari Pandiri; Subrahmanyasarma Chitta (Journal for ReAttach Therapy and Developmental Diversities, 2023)
The increasing frequency and severity of natural disasters, coupled with the growing challenges posed by climate change, necessitate more efficient and responsive systems for managing risk and providing financial relief. Traditional insurance models often struggle with timely payouts and high administrative costs, especially in the aftermath of large-scale events. This paper explores the potential of AI-driven parametric insurance models as a transformative solution to these challenges. By leveraging advanced algorithms, real-time data analytics, and automated processes, parametric insurance enables rapid, data-driven payout mechanisms based on predefined triggers, such as temperature thresholds, rainfall levels, or earthquake magnitude. The integration of artificial intelligence enhances risk assessment, pricing accuracy, and claims verification, offering a scalable and transparent alternative to traditional indemnity-based insurance. This model not only reduces operational costs but also improves accessibility and fairness in climate risk management. We examine the technological underpinnings, regulatory considerations, and potential societal impacts of AI-powered parametric insurance, proposing it as a critical tool in mitigating the financial impacts of natural disasters in the face of a changing global climate.