Dynamic Exposure Aggregation and Automated Risk Scoring: AI-Based Systems for End-to-End Insurance Risk Management Automation

Authors

  • Daniela Rus Professor of Computer Science and Electrical Engineering, Massachusetts Institute of Technology (MIT) Author

Keywords:

dynamic exposure aggregation, automated risk scoring, systems, end-to-end insurance risk management automation, machine learning

Abstract

Insurance underwriting, the process of identifying a risk, determining the size and likelihood of loss, and deciding what the policy terms and prices should be, has been a tool to meet the goal of insurance, i.e., mitigating predictable risk. However, insurability and insurable risk have grown more complex due to changes brought about by technological innovation like the Internet of Things, blockchain, telematics, fintech, and peer-to-peer insurance.

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Published

30-04-2025

How to Cite

“Dynamic Exposure Aggregation and Automated Risk Scoring: AI-Based Systems for End-to-End Insurance Risk Management Automation”. Journal of Science & Technology, vol. 6, no. 2, Apr. 2025, pp. 12-19, https://www.thesciencebrigade.com/jst/article/view/703.

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