Modelling natural catastrophes to help fight climate change

Abstract

Kita provides insurance to mitigate risks in carbon dioxide removal projects, assisting them in attracting investors and scaling up to tackle the challenge of climate change. This talk explores how Kita utilises satellite data to assess the impact of natural disasters on ecosystems and their capacity to sequester carbon. We also examine the areas of active research within Kita, including using large language models to conduct technical and financial analyses of project design documents, predicting political risks and potential policy changes that could disrupt progress, and employing machine vision to create high-resolution wildfire risk maps.

About the speakers

Mansi Agrawal is a Data Scientist at Kita, specialising in risk modelling, portfolio assessments, and performance benchmarking for carbon projects. With expertise in machine learning, remote sensing, and GIS, she develops data-driven solutions to quantify risks and enhance transparency in the carbon markets. She holds a Master’s in Data Science from City St George’s University of London, where she researched wildfire risk and built a machine-learning model to classify aerial imagery by wildfire risk levels.

Dr Paul Young is the CTO and co-founder of Kita, the carbon insurance specialist. Kita aims to accelerate investment in high-quality carbon sequestration projects through insurance products that minimise transaction risks and protect the performance of carbon credit investments.  Paul holds a PhD in Cosmology and has twenty-seven years of experience in asset management, FinTech, and data science. Before Kita, he co-founded a hedge fund, oversaw multi-billion-dollar AI-driven investment portfolios, and co-founded an AI-based fintech startup that was successfully acquired by Nasdaq in 2017.