Climate Risk Analytics

Analytics for better climate predictions

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

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Market Sizing

The Climate Risk Analytics market in the US could reach USD 4.8 billion–7.1 billion by 2030

Conservative case

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Base case

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Expansion case

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Market Mapping


Startups using AI and machine learning (ML) models were most common

Startups in the industry operate across six distinct segments. The most common as at November 2022 were short- and long-term next-generation weather analytics startups using AI/ML models. The majority of the startups in this industry as at November 2022 were at a seed or early stage, with only a handful of startups in the growth 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. 

The Disruptors


Only a handful of disruptors with more than USD 100 million funding

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 2022. Descartes Underwriting, One Concern, Gro Intelligence, 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 2022, these startups had raised nearly half of the total funding for the industry. 

Funding History

Competitive Analysis


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Product Overview
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Company profile
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Incumbents


Most incumbent activities are in the long-term climate risk analytics: AI/ML space

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, which is under development, 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. 

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Notable Investors


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Market Sizing

The US addressable market for Climate Risk Analytics is estimated at USD 11.6 billion

The total addressable market (TAM) refers to the total revenue opportunity available for a product or a service, while the actual market is the market size based on revenue projections.
The TAM and actual market for the US climate risk analytics industry is estimated separately for the following two categories: 1) the short-term weather analytics segment, which includes the use of AI/ML and other next-generation technologies for weather forecasting for up to 14 days, and 2) the long-term climate risk analytics segment, which includes the use of AI/ML and other next-generation technologies for longer-term climate risk predictions and the use of such data in parametric insurance and climate risk rating activities, among others. 
The TAM for the US climate risk analytics industry is estimated to be USD 11.6 billion (see Appendix for details). The actual market was estimated to be USD 1.8 billion in 2023 and is expected to grow at a seven-year CAGR of 18.6%, reaching USD 5.9 billion by 2030 (a penetration rate of 51%).

Summary

Our expansion case expects the market to grow at a seven-year CAGR of 21.6% to reach USD 7.1 billion by 2030 (a penetration rate of 61.0%). Adoption of climate risk analytics solutions by industries other than what we have considered (agriculture, mining, finance and insurance, construction, real estate, sports, aviation, logistics, utilities) would be a potential upside. Our conservative case expects the market to grow at a seven-year CAGR of 14.9% to reach USD 4.8 billion by 2030 (a penetration rate of 41.0%) due to potentially slower AI adoption than expected.

Appendix: TAM calculation by segments

1. Short-term weather analytics

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