AI-Powered Risk Assessment in Natural Catastrophe Insurance.

Authors

  • Ravi Teja Madhala Senior Software Developer Analyst at Mercury Insurance Services, LLC, USA Author
  • Sateesh Reddy Adavelli Solution Architect at TCS, USA Author

Keywords:

predictive analytics, climate modeling

Abstract

Natural catastrophe insurance is essential for shielding individuals, businesses, and governments from the financial repercussions of earthquakes, floods, and hurricanes. However, traditional risk assessment methods need help to keep up with these events' increasing frequency & complexity, driven by climate change, urbanization, and environmental degradation. Artificial Intelligence (AI) and machine learning (ML) are emerging as transformative tools to address these challenges, revolutionizing how insurers assess risks, predict impacts, and design policies. AI models, powered by vast and diverse datasets, including historical disaster records, satellite imagery, climate simulations, and real-time weather data, enable precise risk predictions by identifying patterns and trends that were previously undetectable. These insights allow insurers to create more accurate catastrophe models, tailor coverage to meet individual needs and improve pricing strategies, ensuring fairness and affordability for policyholders. Beyond risk assessment, AI enhances underwriting processes by automating complex analyses and streamlining claims management, resulting in faster resolutions and reduced operational costs. For insurers, these advancements lead to better risk exposure modelling, optimized capital allocation, and improved regulatory compliance. Despite its immense potential, integrating AI into natural catastrophe insurance raises significant ethical and operational concerns. Data privacy, algorithmic biases, and lack of transparency must be addressed to foster trust and ensure equitable outcomes. Additionally, the reliance on AI demands a balance between automation and human oversight to uphold accountability and prevent unintended consequences. Collaboration between insurers, technology developers, regulators, and policymakers is crucial to establishing robust frameworks for ethical AI use. By responsibly leveraging AI, the insurance industry can evolve to meet the challenges of a rapidly changing world, offering enhanced resilience, better protection, and greater peace of mind to those at risk of natural disasters.

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Published

05-09-2023

How to Cite

[1]
Ravi Teja Madhala and Sateesh Reddy Adavelli, “AI-Powered Risk Assessment in Natural Catastrophe Insurance”., Australian Journal of Machine Learning Research & Applications, vol. 3, no. 2, pp. 842–867, Sep. 2023, Accessed: Jan. 04, 2025. [Online]. Available: https://sydneyacademics.com/index.php/ajmlra/article/view/229

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