Development of the Neural Network-Based Index Insurance : A Focus on Climate Change Risk Management

This project focuses on enhancing agricultural resilience to climate change by incorporating neural network-based optimization into weather index insurance designs. By utilizing advanced machine learning techniques, the initiative aims to improve the accuracy and appeal of insurance products for the agricultural sector, which is highly vulnerable to climate-induced weather unpredictability. The collaboration involves academia and industry partners, seeking to address current challenges such as high basis risk and low adoption rates of existing insurance models. The goal is to offer practical solutions that improve risk management in agriculture, ultimately contributing to food security and the stability of agricultural communities in the face of climate variability. Furthermore, this project will transcend the limitations of existing research by adopting generative models, a subfield of deep learning, for analysis.

Faculty Supervisor:

Yang Lu

Student:

Partner:

Ewha Womans University

Discipline:

Mathematics

Sector:

Artificial Intelligence; Finance and Insurance; Sustainability & the Environment

University:

Concordia University

Program: