Climate Risk Has No Standard, and That Costs Everyone

I have spent my career building risk systems for the world's largest financial institutions. The work is precise. It is expensive. It is designed to protect capital, and it does that job well. What I have come to believe is that the same rigor needs to exist everywhere, not just where the money is.

Climate change is no longer a future scenario. It is a present condition, and it is accelerating. The World Economic Forum identifies geoeconomic confrontation as the top global risk for 2026, with extreme weather ranked as the most severe long-term risk through 2036. Environmental risks dominate the long-term outlook, and the report notes that these risks will be felt most severely in developing countries with the least capacity to adapt.

The pattern is not subtle. The last ten years have been the worst ten years on record. Each year has broken the previous year's records. The volatility is increasing, not plateauing. The coming year of extreme El Niño conditions can produce hurricanes that are not more numerous but more forceful, sea-level damage that is more severe, winds that are stronger, and turbulence that disrupts industries far removed from the weather itself.

The long-term consequences are already visible. The UNHCR reports that nearly 4 million people have been displaced across the Central Sahel, roughly double the number from 2020. Climate-related shocks are compounding the crisis, eroding livelihoods and limiting access to water and land. In the Pacific, island nations face the possibility of losing their physical territory entirely. In Europe, heat waves kill thousands of people who live in old buildings without air conditioning. In Asia, food supply chains are under pressure from drought and flooding.

I believe the problem is not a lack of understanding. It is a lack of availability and standards.

Consider how we measure risk today. The world's largest banks and insurers have sophisticated tools. They can model the physical risk of a flood, a wildfire, or an extreme heat event at the level of a single asset. They can run thousands of scenarios and produce probability distributions rather than single forecasts. This capability exists. It is mature. It works.

Now consider a small farm in Zambia. Eighty percent of Africa's food is grown on small farms. Those farmers typically have no insurance. They have no way to model what the next decade of climate volatility will do to their yields. They cannot plan for a drought they cannot see coming. The tools that exist are priced for institutions, not for the people who are most exposed.

That is not a technology problem. It is a distribution problem. The same engine that powers a large financial terminal can run on a laptop. The same climate simulations that inform a bank's capital planning can inform a farmer's decision about what to plant and when.

I believe the answer is to build a standard. This is what we are working on at ClimateRiskCommons. Not a proprietary product. An open framework that anyone can use, anywhere, in any language. A common way of describing assets, hazards, and scenarios so that a student in Zambia can build a model and share it with a researcher at Stanford, and both can understand what the other has done. A shared reference pipeline that runs end to end on a laptop. An open specification that makes results comparable across organizations.

This has been done before. The operating system that runs most of the world's servers started as a free, open-source project built by one person who decided that the existing options were too expensive for ordinary people. It was dismissed. It grew. The network of contributors made it better than any single company could have made it alone. The same principle applies here. When a million people are testing a model, it improves faster than when a hundred people are.

The open standard is free for non-commercial research, teaching, and planning. The largest financial institutions using it for commercial purposes are charged. What I am proposing is free access to infrastructure where it is needed most. They both have access to the same compute engine. That is how the ecosystem grows.

If we get this right, the outcome is a world where climate risk can be measured by anyone, anywhere. A city planner in Mozambique can screen infrastructure investments for flood exposure. A university researcher in Brazil can stress test a portfolio against climate scenarios. A farmer in Zambia can access the same probability distributions that a global bank uses for drought.

In short, we democratise access to a world-class standard climate physical risk measurement.

If we do not, the outcome is the one we are already living. The people with the least capacity to adapt will bear the greatest cost. The gap between the insured and the uninsured will widen. And the tools that could have helped will remain locked behind the price of admission.

I do not believe we can prevent every climate impact. I do believe we can give everyone the same ability to see what is coming and prepare for it. The standard is how we stop guessing and start sharing.

About The Author

Ron Dembo is the Founder and CEO of RiskThinking.ai, a Toronto-based climate risk analytics firm. A former Yale professor, he has spent his career building risk systems for financial institutions and is the creator of the Climate Digital Twin. His work focuses on making climate risk measurement accessible to researchers, planners, and communities worldwide.