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Editorial Advisory Board

  • Professor Andrea M. Armani, University of Southern California
  • Ruti Ben-Shlomi, Ph.D., LightSolver
  • James Butler, Ph.D., Hamamatsu
  • Natalie Fardian-Melamed, Ph.D., Columbia University
  • Justin Sigley, Ph.D., AmeriCOM
  • Professor Birgit Stiller, Max Planck Institute for the Science of Light, and Leibniz University of Hannover
  • Professor Stephen Sweeney, University of Glasgow
  • Mohan Wang, Ph.D., University of Oxford
  • Professor Xuchen Wang, Harbin Engineering University
  • Professor Stefan Witte, Delft University of Technology

Video: Helping companies address extreme weather as they would other financial risks

Video: Helping companies address extreme weather as they would other financial risks

Josh Graham is CEO and co-founder of Ehab, a weather intelligence platform helping infrastructure, insurance and finance sectors turn extreme weather into better decisions. He joined me on a recent episode of The Impact to discuss how best to take advantage of changing times and shifting markets.

Jeff Gitterman: It’s amazing because in the markets, they use forward-looking data sets on everything to talk about political risk and all kinds of market-related risks that, at best, historically has had less than a 50% rate of being right on those predictive analytics. And yet the markets eat all that data up.

And climate data, which has been incredibly more accurate than any of the financial models that are used by a lot of the big risk firms, has been the last thing to be adopted. 

Talk to me a little bit about the fact that you look at traditional financial metrics, and now you’re looking at these companies that you are seeing on the street look at weather as just as important as a traditional financial metric, and how are your data sets pulling that in?

Josh Graham: Just take agriculture for example. We all know that weather is going to impact my grapes or my soybeans or whatever it might be, but it’s actually, I think it’s up to 70% for certain crops can be the effect of weather contributing factor towards its yield. And in many other industries, it is between 15% and 20% of the total cost of something can be influenced heavily by weather.

And so I think from a finance perspective it’s been really difficult to get granular enough information quickly enough when you are not necessarily a meteorologist. So some of the products that trying to bring in are around, well, just how do you lower the barrier to entry? How do you make it easier?

And that’s, I think, where AI comes in because as we all know, it becomes quite easy to use a tool if all you have to do is talk to it instead of learning that I have to click this button and click that button. So for us, the data is there, but to a get the data and then structure it into a way where you can genuinely get insights from it, regardless of the industry you are in. That’s actually the tricky part.

Jeff G: So let’s take a peek into the future. I mean, you’re using AI, you’re using large language modeling. What do you see 2, 3, 5 years out from now in the world of climate risk being adopted by the financial industry, the insurance industry? What’s your crystal ball telling you?

Josh G: I honestly get the sense that there is a momentum building with these industries where they’re genuinely taking it more seriously and thinking that it’s something that needs to be a go-to
business, as usual, one of many data points where they make decisions, but of course a super important
data point that influences the outcomes that they’re going to have.

Watch the full interview

More video from Jeff Gitterman: Waking up to climate risk in the muni market

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