Home

Matthew Dixon

Likes
92
Date
2022/05/12
Image Link
Empty
ML Score
5
Job
CFX Labs Inc. | Co-Founder
Content
For me personally, one of the holy grails is to tie machine learning and finance to climate change - that is using ML in finance to tackle some of the most challenging problems of our time. In addition to ESG investing, providing financial protection against climate risk is another key ingredient - we need to protect society while figuring out our sustainability transition plan. Natural disasters could otherwise wipe out budgets set aside for R&D, e.g. Hurricane Katrina devastated New Orleans. That, perversely, over time gives fossil fuel companies the upper hand.Destruction -> poverty-> lack of education-> poor personal sustainability hygiene and lack of local opposition to fossil fuel companies (fossil fuel jobs>perceived environmental damage)While not a climate solution, there is a growing contingent claim product area for managing climate change and natural disaster risk and one area where richer datasets (e.g. satellite imagery) and ML can ultimately make a significant difference in ensuring fair pricing and more robust uncertainty quantification. Our latest technical paper on embedding clustering into a unified Hierarchical Bayesian modeling framework for catastrophe and interest rate risk premia adjusted CAT bond pricing is available on arXiv: https://lnkd.in/dQivqGXW This is joint work with co-authors Chatterjee and Domfeh. #climaterisk #machinelearning #environmentalfinance #bayesianstatistics #insuretech #quantitativefinance #weatherforecasting Peter Adriaens Dixon Domfeh Morton Lane Runhuan Feng, PhD, FSA, CERA Todd Ringler Swami Sethuraman Joydeep Lahiri Maura Feddersen Larry Eisenberg Dr. Sebastian Rath Richard Matsui Lawrence Habahbeh
Property
Empty
Link
https://www.linkedin.com/feed/update/urn:li:activity:6930361958030270464
Comments
7
Type
Post
Profile
https://www.linkedin.com/in/mfrdixon/
TOP