NH032-0006
Fast and Efficient Climate Risk Estimation of Future Portfolio Risk Exposure for Financial Institutions

Tuesday, 15 December 2020
Poster
Tristan Ballard, Gopal Erinjippurath and Eva Linghan Scheller, Sust Global, London, United Kingdom
Abstract:
Financial institutions are playing an increasing role in the low-carbon transition by taking steps to accurately estimate, price, and disclose future climate risk. By quantifying their exposure to climate risks, financial institutions can more effectively allocate investments, avoid stranded assets, and track adherence to Paris Agreement goals and shareholder commitments. However, it remains difficult for these institutions to assess climate related risks across a portfolio of assets and across different benchmark warming scenarios. To that end, we developed an end-to-end framework for quantifying annual, asset-level climate risk for three climate hazards: wildfires, inland flooding, and heat waves using simulations from global climate models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). We quantify climate risks from 2020 to 2100 under both high-emissions (SSP5-8.5) and medium-emissions (SSP2-4.5) warming scenarios. To facilitate analyzing and visualizing this suite of risks, we also developed a customizable dashboard application. We demonstrate the feasibility of these risk assessments with a portfolio of 5,000 U.S. assets spanning land, commercial, industrial, and residential sectors. We find this asset portfolio, with a combined market valuation over US$25 billion, faces significant spread in climate risk exposure, including differential impacts by climate hazard and considerable spatiotemporal variability. Moreover, we identify particularly high-risk assets as well as assets facing decreased risk, a useful tool for balancing portfolio risk. Ongoing work will incorporate climate hazards such as cyclones and coastal flooding as well as additional risk score metrics developed in consultation with institutional and commercial partners. Through this research workstream, we intend to enable financial institutions with fast and efficient exposure estimation, loss modeling, and risk assessment tools to translate climate hazards and policy scenarios into scientifically rigorous, asset-level climate risk indicators.