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Climate Risk Analytics
Overview
Climate risk analytics attempts to outperform legacy numerical weather prediction (NWP) models with next-generation AI-driven predictive analytics tools, among other technologies. Advancements in AI and data sciences have made it possible to identify more granular and hyperlocal patterns in weather data, enabling more accurate and longer-term climate risk forecasts—in some cases up to 80 years into the future. This is against a backdrop where even a seven-day legacy forecast is considered to be only 50% accurate.
The US SEC climate disclosure rule and the increasing incidence of natural disasters and related losses have been key drivers for the industry. In addition, AgriTech and InsurTech have been early adopters of climate risk analytics solutions and increased incumbent activity is also a key driver. However, the limited accuracy and location biases of AI weather models remain a drawback.
Industry Updates
Market Sizing
The Climate Risk Analytics market in the US could reach USD 4.8 billion–7.1 billion by 2030
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Market Mapping
Startups in the industry operate across six distinct segments. The most common were short- and long-term next-generation weather analytics startups using AI/ML models. The majority of the startups in this industry were at minimum viable product and go-to-market stage, with only a handful of startups in the expansion stage. Most technologies are still emerging and at pilot scales.
Incumbent activity was predominantly seen across the long-term climate risk analytics: AI/ML segment, with notable in-house developments undertaken by NVIDIA, IBM, and PwC.
Short-term weather analytics: AI/ML
Short-term weather analytics: Other
Long-term climate risk analytics: AI/ML
Long-term climate risk analytics: Other
Long-term climate risk analytics: Parametric insurance
Climate risk rating
The Disruptors
The industry is still relatively young, with most of the leading startups in this space having been founded after 2015. B2B software-as-a-service (SaaS) is the most common type of business model, where organizations subscribe annually to weather and climate risk analytics services. Parametric insurance companies are an exception; they use climate risk modeling for internal use to price insurance contracts.
Short- and long-term weather analytics utilizing AI/ML models were the two highest-funded segments as of November 2024. Tomorrow.io, Descartes Underwriting, One Concern, Climavision, and Jupiter Intelligence were the highest-funded startups that raised either more than or close to USD 100 million in funding. As of November 2024, these startups had raised nearly half of the total funding for the industry.
Funding History
Competitive Analysis
Incumbents
Most incumbents offer long-term climate risk analytics solutions by leveraging AI/ML models to develop their own climate modeling solutions. This includes NVIDIA’s digital twin of Earth known as Earth-2, IBM’s AI-powered Environmental Intelligence Suite, and PwC’s Physical Climate Analytics tool powered by Jupiter Intelligence. Google’s AI-subsidiary DeepMind has developed a rain prediction model–to derive short-term weather analytics–called “Nowcast.”
A vast majority of incumbent partnerships and M&A activity are also in the long-term climate analytics: AI/ML segment, with disruptive climate intelligence startups such as RMS (acquired by Moody’s) and Four Twenty Four (also acquired by Moody’s) being acquired by larger consultancy companies.
Notable Investors
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Overview
Climate risk analytics predicts physical climate risks
The duality of climate risks: Physical vs. transition risks
