Cervest

The prevalence and increasing frequency of climate-related extreme events such as heavy storms, extensive flooding, severe droughts, widespread wildfires or intense heat waves opens a nascent but fast-growing market opportunity for companies that help manage and mitigate their consequences. 

The impact of these climate-related events is universal, pervasive and expensive. It affects everyone, everywhere, in every industry. Hundreds of billions of dollars of assets are at stake, and the overall market for climate adaptation is set to double to $2 trillion a year within the next five years.

Protecting these assets and sustaining life on earth requires actionable data. And while scientific data on specific hazards and events exist, it remains sparse, fragmented, and siloed, which makes it challenging to draw any insight from. This is the core challenge Cervest is tackling.

We were introduced to Iggy and his team by our networks, and were struck by their vision of the world, the depth of their research and the sharpness of their market analysis.

Cervest’s core value proposition is anchored in its modeling. In contrast to most contemporary ML “black box” approaches, Cervest’s team proceeded with the early conviction that providing asset-level and decision-ready insights requires applying a healthy mix of traditional machine learning and mechanistic statistical analysis.

Integrating known physical processes and relationships into their models helped decrease noise and reduce uncertainty as the team integrated 70+ otherwise siloed, disconnected data sources.

Furthermore, while existing data sources structure data according to arbitrary grids superimposed over the surface of the Earth, Cervest had to implement bespoke versions of the models in a probabilistic way, focusing on data assimilation. They employed Bayesian non-parametric modeling to make inferences and determine best-case probabilities and correlations between risks (signals) at any specified point, especially when information isn’t defined at that particular point.

All of this was notably made possible by Cervest’s deep Earth Science expertise. With climate and earth scientists on their core team, they can model multiple physical sciences and bring methodologies across disciplinary boundaries to jointly score risk levels at scale.

The result is a queryable global asset inventory offering an independent asset rating solution, with on-demand and personalized insights and analyses on asset-level risks. The Cervest team had shown that they could work with large corporations and potential clients. Now, dozens of large corporations are using their solution to map out asset portfolios and build resilience.

Cervest's solution has the potential to become an essential piece of technological infrastructure in the emerging climate risk market, as companies and governments worldwide seek to mitigate the impact of the climate crisis on their assets, and are increasingly required to report on physical risk.