In February 2021, a one-week long cold snap in Texas, USA, is estimated to have cost $195bn in lost income and long-term economic outputs from supply chain failures. More than 4.5m homes and businesses were left without power. Over 100 lives were tragically lost. More recently, we’ve seen record breaking temperatures due to extreme heatwaves gripping cities around the world, resulting in electrical grid failures, extreme drought, and devastating wildfires.
Lukky Ahmed, Chief Executive Officer of London-based startup Climate X says “It simply doesn’t make sense that climate risks aren’t factored into pricing, valuations or investment strategies. The limited data available in the market was fragmented or assembled in ways that didn’t stand up to our scrutiny, so we decided to partner with leading climate scientists and academia to create it ourselves.”
The firm uses a blend of physical risk models and machine learning to automatically project how extreme weather events linked to climate change could impact millions of specific assets or locations anywhere in the world, up to 80 years into the future. To bring the impacts into the real-world, they also calculate how exposure to extreme weather events could impact the value of assets.
Climate X uses state-of-the-art climate projections and, where applicable, they downscale them to a high-resolution as precise as 2km x 2km – that is effectively 400 different weather patterns over London. The solution can deal with any type of climate scenario: regulatory (e.g. recent Bank of England climate stress), policy (Paris Agreement, Network for Greening the Financial System) or client-derived (e.g. country-specific with socio-economic calibrations). The climate models allow them to extract extreme future weather events until 2100 that may cause a variety of hazards on the ground.
Climate X then combine the extreme weather patterns with remote sensing data from a number of satellites, reducing dependency on local data and helping deliver past and real-time accuracy (up to 1mx1m) of the extent and severity of possible risks, including floods or geo-hazards. Where the data is scarce, machine learning is selectively deployed to enable approximate model inputs from areas with similar characteristics.
With Central Bank requirements for financial institutions to undertake climate scenario analysis and stress testing for the first time, the company is set to release its final product to the UK market by the end of 2021, with plans for rapid international expansion in 2022.
Kamil Kluza, co-founder and Chief Product Officer, said “Climate X is bridging a gap between regulatory requirements and the latest technology. We’ve built a ‘glass box’ solution combining remote sensing, a digital twin of the Earth and machine learning. By carefully balancing these components, we help satisfy both regulators, who require transparency, and users, who need detailed and understandable climate intelligence at asset-level scales.”
Climate X has already garnered attention from globally significant institutions, across multiple industries, joining their Proof-of-Concept programme over this summer taking advantage of the opportunity to see Climate X’s data in action. The firm has just completed its pre-seed raise of $1.5m. The round was oversubscribed.
For more information visit Climate X