Machine Learning Approach To Weather Insurance

Harvester in a field

Researchers co-led by NTU's Nanyang Business School have used machine learning to design a more cost-efficient insurance contract that could better protect farmers against weather risks arising from climate change.

The research team used neural networks to uncover intricate relationships between weather variables, such as temperature and rainfall, and crop production losses.

They then designed an artificial intelligence-based weather index insurance contract for farmers using the results of their study. The new contract could improve policyholders' wealth by nearly 5%, with a 37% lower price compared to the current average price considered in the study.

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