Climate Risk Meets Finance: Modeling the Future of Real Estate with First Street

You're listening to Climate Rising, an official podcast of Harvard Business Schools, Business and Environment Initiative. And it's very eye-opening when you start to look across, get away from the climate service vendors like First Street, you go to more of a general risk group like a reinsurance company. And you look to see how those risks from extreme weather events now are as big or bigger than anything else that they're worried about. Climate risk is not an issue. It is the subject across risk management now. This is Climate Rising, a podcast from Harvard Business School. I'm your host Mike Toffel, joined by my colleague John Mulliken, senior lecturer at Harvard Business School. Thanks for joining me as a co-host, John. Thanks so much for having me, Mike. Today's episode is part of our series on AI for Climate, where we explore how artificial intelligence is shaping how companies understand and respond to climate risks. Our guest is Ed Kerns, chief science officer at First Street, a company that uses advanced data and analytics to assess climate risk across assets, infrastructure, and communities. We'll explore how AI is being used to better understand climate exposure and informed decision-making. And what it means for businesses, investors, and policymakers navigating an increasingly uncertain climate future. Here's our conversation with Ed Kerns, chief science officer at First Street. Let me take a minute to tell you about another HBS podcast. If you're interested in how business leaders make decisions that shape industries and drive impact, I think you'll really enjoy listening to the founder mindset where the Reza Satu, the brand new podcast from our colleagues at Harvard Business School Foundry. On climate rising, we often explore how companies tackle complex challenges. The founder mindset takes you inside those decisions. Reza sits down with founders like Reese Witherspoon, Kevin O'Leary, and Tim Ferris, and asks them to walk through how they actually make decisions in real time, especially under pressure. These conversations go beyond success stories. They dig into the trade-offs, the risks, and the mindset behind building something from the ground up. If you're curious how leaders navigate uncertainty and turn ideas into impact, this is a great lesson. Follow the founder mindset with Reza Satu on Apple podcasts, Spotify, YouTube, or wherever you get your podcasts. I'm Samir Patel, Editor and Chief at Quanta Magazine. Our mission at Quanta is to cover what we call basic or fundamental research in science and math. That means the kind of work that's driven by curiosity and discovery and the search for knowledge. We're interested in how and why everything around us works the way that it does. On our brand new show, The Quanta Podcast, you'll meet the writers and editors behind the magazine, and together we'll explore the biggest ideas and the tiniest details. Join me for the Quanta Podcast, your weekly dispatch from the frontiers of science and math. Ed, thank you so much for joining us here on climate rising. Thanks for having me. So why don't we begin with a very brief introduction to your role and a bit about how you got there. I'm a scientist, a monoscientographer by training. I work at a place called First Street where we are connecting climate change to financial outcomes. I got here by a long career in science, both at the academic level, University of Miami, and also with the federal government, particularly with the National Oceanic and Economic Sphere Administration, we're dealing with a lot with climate data and climate outcomes. I was inspired by the difficulty in explaining climate change impacts to the American public and to American businesses to try to find a different way of doing that. And that's why First Street exists. So I joined First Street about six years ago, after 15 years with the federal government to work on climate. Great. And so let's talk a bit about First Street. So what does First Street do? Who are its customers at a very high level? We're going to dive in for sure during the conversation. We translate how climate change is impacting physical risk. So this could be flood, this could be wildfires, this could be winds, translating that into financial outcomes. So if people need to be making decisions either for themselves and their home, or perhaps the business that they run, then we provide the tools which they can understand the climate science, translate that risk into some kind of financial measure that they can then use to make decisions about how they're going to be impacted. Got it. And is this focusing primarily or exclusively on real estate? Or are you also thinking about supply chain and agricultural fields and things like that when you're thinking about these risks? Yes, so we're looking at physical risk as it impacts buildings and properties right now. This is starting to also go into infrastructure and also supply chains. We have stopped short on things like agriculture, which already has a very active industry looking at some of these things. So there are certain pieces of it that we haven't gotten too deep into yet, but we are describing the hazards for everywhere on earth. They can be translated into these other things as well. But right now we have seen to have found a good product market fit with real estate and with investors in real estate, and that's where we're going right now. Great. So John, you want to dig into the science of physical risk? That's great. I'm really interested in how you compare to some of the existing models. I mean, there's traditional risk tools. I think a lot of people are familiar with FEMA floodmaps and they were really built for a stable climate. And so I'm just wondering how do you design a model that's explicitly forward looking? When it captures what one of these assets you're looking at is going to face in 15, 30 years, not just what it faced historically. Yeah. And the FEMA floodmaps are a great example of the challenge in front of us, right? So FEMA floodmaps were created, like you said, for a stationary climate. They are looking only at river and flooding and surge flooding. They don't take an account in heavy rainfall, for example. But what we've discovered as a country over the last 30, 40 years is that a very large percentage, about 40% of flood claims are coming from outside FEMA flood zones in the US. It's been very consistent over the last couple decades, right? And the question is, well, why? What are we missing? What's missing from this equation? And it's been largely that the lack of heavy rainfall flooding has included as part of the FEMA flood mapping. If you don't include rainfall, you're missing a big piece of the puzzle. It also happens to be that piece of the puzzle that's changing the most with climate change right now because of the relationship between air temperature and water vapor in the air for every one degree centigrade that you increase air temperature, you can cram in 7% more water vapor. And so if you're living like on the east coast of the US and you think that rainfall has gotten heavier over the last couple of decades, you are not imagining that. It is demonstrable that that is what's happening, right? So at first street what we're doing is we're relying on the physics-based model. So for flood, we're going to drive a flood model that shows how water will move over their surface and we're going to drive that with rainfall. And we're going to drive with river and flooding. And we're going to drive with surge flooding. And we're going to drive it with sea level rise, bringing all these things together and say, well, just how deep can the water get at your business? How deep can the water get at your home or at the infrastructure? What's that look like? And then we can do it probabilistically, look at different what it's called in the business return periods. How often you would see this kind of storm come back or this kind of configuration come back. And you may hear of like the 100-year storm or the 500-year storm. So those equate to a 1% annual risk or a.2% annual risk. So you can do this probabilistically and rolling the dice and see what are the chances of having water that's going to come into your home this year and how that's going to change in 30 years or 100 years with climate change. And so by using these physics-based models, we can map out those probabilities to a great degree of accuracy and arm you with that kind of information that you need to make a decision. And I imagine that there's pretty deep uncertainties still in these climate models that you have to face scenarios in which things can behave non-linearly in which you can see that the trajectory is going to change over time in perhaps in ways that might be hard to predict. How do you handle those ways in which the climate system begins to move in ways that it has historically moved in response to what we've put in the atmosphere? Yeah, so we are focusing on those things for which we do have predictive capability. So that is air temperature in particular. We know how that's changing sea level rise, another good one. And by looking at the studies of hurricanes and exotropical cyclones, it's up we can see in the climate models and there are dozens and dozens of climate models that have been produced. We can use groups of them. So we're basically doing ensemble modeling, right? We're taking the averages across multiple dozens of climate models to drive down any one models uncertainties. And then we're looking over span of 20 years. So when we look ahead 30 years, we're taking plus or minus 10 years around that 30-year target. So again, we're averaging many years together. Again, driving down the uncertainties. That's great. I was wondering about, you know, you've mentioned a number of different types of climate risk. You've got, you know, fire and you've got flood and so forth. And you mentioned how as temperature goes up, the atmosphere can hold more moisture. I'm interested in how these different types of risk interact. How do they compound or they additive? How do acid owners think about the combination of all these different risks? Yeah, they're actually in phase with each other, right? There's so many different oscillations within the climate system. Your listeners may have heard of some like El Nino, right? They may not exactly know what El Nino is, but this is a type of climate oscillation. There's literally dozens of them. You know what that lantic oscillation or whichever, pick your favorite oscillation. But what that does is it ties climate events and climate risks together on like continental even global scales. And so when you're modeling climate, it's one of the challenges, right? Is you have to consider it as a global system. And all these climate models, I was just mentioning that is how they're simulating climate. They're looking at the global expanse. It's very difficult and very expensive to do, but that is the current state of the art and modeling. So by looking at these things, not as isolated events, but looking at them together, yes, sometimes they do compound. And so what we've done at first street is beyond modeling the risk from that particular hazards they flood and wind, is then we look at the correlation between those perils as we've seen in observations over the last 20 or 30 years. And that is something that you again can measure and you can put a number on it, right? And then you can map that correlation into future estimates of losses. So if you know that these areas are under certain climate conditions, it always being together or maybe they're beating apart, maybe one thing might make another type of risk more likely or make it less likely. So you may be compounding losses and risk or you may be diffusing that. But all those evidence for that is in the observed record. And we have very good observations of these things over the last couple decades. So we lean heavily on the observations of the past and we're mapping that into the future with these correlations already in place. - So, and I wanted to ask a question based on what you said a moment ago, which was that you have this ensemble model, which is sort of a model of models. And is that the IP, the intellectual property that First Street offers because you're not developing first-order models, you're relying on other models, but what you're doing is assembling them. Is that what you're doing? Are you also offering yet more new models or tweaked models? Because you were talking about comparing predictions to actuals, which makes me think about machine learning and now you're coding it and maybe improving the models. So, which are you doing or maybe some of each? - It's some of each. So, the averaging across models is nothing particularly novel. That's a very common method. Your listeners may, if they live on the East Coast or Gulf Coast of the U.S., I'm sure they've looked at Hurricane Forecast before. And something that the National Hurricane Center does is that the use ensemble modeling also, too. And they may have seen what we call spaghetti diagrams in the business, right? Lots of different models. And the forecasters then will say, "Okay, well, you've got 15 different models that say the hurricane is going to go here. We're going to average them together and we're going to have our cone of uncertainty." And so, that has been a very effective approach. Not just figuring out where the hurricane is going to go, communicating that to the American public. So, kudos to the hurricane center, kudos to the National Weather Service and Noah that has continued to improve this, right? So, it's a very effective way of moving this forward. Now, we're faced with a challenge of taking these climate models and making them useful for individuals. And so, to do that, as I said, the climate models are being run on a global resolution and necessarily because of the computation and cost involved in that, they are relatively coarse in resolution. So, there are 100 kilometers, 50 kilometers. If you think of it like a pixel and a digital image, each pixel is 100 kilometers wide. So, if you're trying to figure out what's happening at your business or that piece of infrastructure or your home, you need somehow to take that information and we call it downscaling, getting down to the finer level. And this is where first street is adding value. And this is where all the work is, is how do you get down to that 30 meter level and wildfire? How do you get down to that three meter level in flood? Because it matters whether it creeps on one side of your house or the other, right? It really matters. And so, we do that by injecting a flood model or wildfire model or wind model between the climate models and then the target, which is an individual building. So, we have to have some way of translating that coarser information into a high resolution prediction that can be useful for people so that you have house to house or business to business differentiation. When building is a little bit higher than the others, I'm like that. So this is something that you don't see very often because it's hard. So in the theme of flood models that we were just talking a little bit about before, they are famous where I should maybe say infamous for having maps drawn with a big border around an area that has flood risk. And everything inside that is binary. You either have flood risk or you don't, right? And it doesn't matter if one of those homes is higher. Maybe it's been raised higher than the other ones and it's going to be above the flood. They just consider them all together because it's simpler to model that way. So what we've done is we've spent the time in the effort to tune and run these physics-based models, not AI, we're using physics-based models because we need to be able to trust that downscaling. We have to understand the physical processes that are allowing that downscaling. Not only that, we have to also be able to trust that 30 years into the future that our projections 30 years are also going to be trustworthy, right? And so the physics is not changing in 30 years or 100 years. Physics is going to be the same, right? Let me take a minute to share a podcast recommendation with you. If you're curious about how work is changing and what business leaders should be doing about it, you should check out the Managing, the Future of Work podcast from two of my Harvard Business School colleagues. Managing the Future of Work offers an inside look at how CEOs, policymakers, and experts are navigating major shifts like AI and evolving talent needs. Such episode gets into the real decisions companies are making from how they hire and train talent to how they adapt to constant change. You might start by checking out their episode with Bank of America's Josh Braunstein on skills-based hiring, developing talent from within, and preparing for what's next. Follow HBS Managing, the Future of Work on Apple Podcasts, Spotify, or wherever you're listening now. At Climate Rising, we often discuss the risks, the policy frameworks, and the strategic shifts required to confront climate change. But what about the success stories already in motion? From NorCal Public Media, an Emmy Award-winning journalist Charles Lloyd comes a fighting chance, a new podcast dedicated to the people and industries actively winning the transition. While headlines focus on the cost of climate inaction, a fighting chance documents the return on investment of climate innovation. Scientists revolutionizing our approach to forests, oil workers securing funds for a green transition, and many others. This isn't just a story about saving the planet. It's a look at the new economy being built today. Fighting chances available to watch on YouTube and Spotify, and streamable wherever else you get your podcasts. You're not the only company that's doing this, and there's been this debate that I've read about that your damage estimates might, in some cases, run higher than other ones that are out there. As a scientist, how do you think about that? Is it better to be more conservative or better to be more aggressive? How do you make the case for accuracy when you're projecting these 15, 30-year risks and you can't perfectly validate them yet? Yeah, so a lot of the differences among the models is what they were created for. So some of these comparisons, and it's great to see that comparisons is not enough of them out there quite frankly, so we need to see more of these done. There is a paper recently looking at some of the insurance industries cat modeling comparisons with first rates. Those models are all built for different purposes. Some are built for the insurance industry. They're built to be calibrated on the loss of themselves, and they're looking at extreme events. They're only looking at the 100 or 500-year events. Now first street, we're looking at risks all the way from, on the coastal areas, the one and two-year, right? Every other year type of thing, so we can resolve things like king tides and stuff like that, right? And then all the way to one and five-year, one and 20-year. So when you're adding up losses, those events with the lower return peer are not as severe, so they don't do as much flooding. But there's a lot more properties that have that risk, and it's more likely to occur. So if you're creating an annual average loss product, which we have done, and you start to include those lower return periods, you will get a lot of losses. There's small losses. They're not extreme, and they're not the kind of losses that the insurance companies are necessarily worried about, right? Because these aren't the things that are going to break the bank for them. But these are the kind of losses that are going to be impacted individual homeowner, or the individual business owner, so they need to be aware of them also too. So we're building the model for a slightly different purpose. And so that's, I think, one of the reasons why we're seeing some of the disparity in some of the loss estimates. Because we have a different target. And so if you start to slice the data more finely looking only at one and one hundred year risk or something like you may see some other differences because the inputs are a little bit different also too. Is there an incentive your clients want to see more risk or do they want to see less risk? No, that's not what I've really perceived in the business. People just want to know really what is the risk? What can I bank on? Because this is a good sign in the community that with climate risk, it's being now looked at not as some esoteric thing. But something is like, oh, this is just another risk that I have to manage for my portfolio or for my business or for my bank. It's just something else that they're managing lots of other kinds of risks. Now climate change now is saying, okay, this is yet another one that I've got to manage. So in the other risk that they're managing, there's uncertainties with those with climate risk, with the physics of the climate system are actually pretty well known. And so majority of the uncertainties actually don't come through this physics-based modeling right now, but they're coming through the damage functions and the loss functions associated with the physical damage and downtime to buildings is a lot of variety. And that's depending upon the types of buildings. So you're seeing a whole resilience industry also too now stepping up to the plate, which is great to see the engineers are coming out and saying, hey, yes, we can help people mitigate for this risk. Because this is the, I think the other thing that's really happened in the last two years is that the talk in the industry has turned away from, is this a risk? Is there transition risk to, oh, yeah, we've got this risk. It's going to happen. It's a sure thing. How do we mitigate it? I think it's maturing. It's becoming a healthier conversation. Yeah. I mean, when people talk about transition risk, typically they're talking about policy or norms changing to price carbon. How does that change the market for renewable energy or for EVs? In this case, what we're talking about, physical risk. That's happening regardless of policy. And the long term, the question is just depending on how much we can mitigate our carbon emissions that will mitigate the amount of physical risk we will face, but we're facing physical risk in some manner, no matter what. It's a really different conversation. It is. It's a sure thing. This past year in New York during climate week, during the UN General Assembly, I'll climate week, a lot of climate people come to New York to have these discussions. And in previous years, I've often had to explain what you just were talking about. The physical climate risk is a sure thing because everybody's talking about the policy, the transition risk, the incurbing carbon, and how can we change the course of all this. And I would have to explain to people that, well, even if you institute a lot of these great reforms that are going to have impact on climate, that we're not going to see the impact of those things for 20 or 30 years because the train has already left the station. This year at New York Climate Week, I did not have to explain that not a single time to anybody. So everybody now is like, oh, yes, it is happening. It has happened. I must prepare. Like I said, I think it's maturing. Great. Well, this conversation about models and science and physical risk, that's really about the product or services that you offer. Let's talk about the customers who are interested in that product. And I think there's a number of them, right? There's real estate investors thinking about assembling their portfolio. There's real estate developers who are thinking about a particular site or there's companies who are thinking about putting a factory, a billion dollar wafer fab. And then there's the consumer side thinking about buying a home, which constitutes a large portion or vast majority in some cases of their savings and for retirement and so on. So take us through a couple of use cases for different customers and how you're engaging with these customers. Yeah. [BLANK_AUDIO] by maybe also explaining at the same time a little bit how first read evolved over the last six years also too. Because when we started releasing our first flood model back in 2020, we were a nonprofit at the time and we were really trying to figure out how to communicate this risk to the average everyday person because we weren't sure yet what that market looked like. But we knew we had to figure out how to create these products and how to communicate them. And so, yeah, some of the first things we had done with flood was yeah, publishing maps on our own website to say, well, this is how it's changing, doing things like simple numerical scores, one to 10 scores, one being good, 10 being bad, to kind of simplify the presentation of that information, like just like I was describing earlier with the hurricane center, how they've managed to communicate uncertainty and risk in a certain way. We were trying that same thing with flood risk. I think we discovered that yeah, there's a big market for that hot there. A lot of people want to know about it. A lot of homeowners are concerned about this because they think they don't have a good view of risk from FEMA or from their local authorities who are not quite sure what it is. And so, they want number one to find out what their risk is. If they find out if they do have risk, then they immediately go to, okay, how is this going to impact the value of my home? So, for most Americans, that's their biggest investment that they've got is the money in their home. And they want to learn how to protect it. How do they get insurance? How much insurance should they have? All these kinds of things. So, we did experience that and then soon thereafter, we discovered certain US federal agencies, whether it's a treasury or the Federal Reserve banking system, Fannie and Freddie FHFA. They were all very interested in this too because they had the same questions. But they were thinking on a large scale, thinking national scale, how much climate risk is inherent in this. And I was also concerned about that. I grew up in Miami and left Miami in 2008 during the big 2008 downturn. I don't want to see that again. I don't want to go through that real estate issues that we had back then. And so, anytime you have a latent risk that's not well-quantified like we had back in the day, there's a risk that this could get bad, right? And so, the Office of Financial Research at Treasury had put out a couple reports, one that looked at Freddie Mac's portfolio with risk. And this came out like in 2023, I believe. And they had analyzed independently how much climate risk was in Freddie's portfolio, which of course is on the backs of the taxpayer. And they discern that, no, the risk was being managed well by Freddie. This was music to my ears. It's like, okay, great. This information that we're putting out there is being used to manage portfolios of real estate and mortgages in a very clever manner so that the risk is diffused and it's not going to spike on us. It's not going to really hurt the housing market like we saw in 2008. So, this is great. Then banks also started to follow along and suit and also worried about their mortgage portfolios. And there was regulation at the time that was, you know, also they were interested in finding out how they're going to meet some of these regulatory requirements that they were facing at the time. And so, we also started talking with banks. And then, of course, with the new administration, there were a lot of changes of priorities and a lot of that regulatory, climate regulatory work was deemphasized or removed. And so, the banks weren't as interested anymore. They didn't feel the urgency anymore. But real estate investors and asset owners, asset managers, now we're starting to step up because of this information that's going more widely known. And they realized, oh, this is a material risk to our portfolio. And whether it's a pension fund or somebody that's really having a longer outlook, they have hold periods that are beyond eight or 10 or 15 years. They are the most concerned about this. And so, we thought, oh, here's a market for this kind of information. But you also have to be able to provide this for thousands of properties. You're not going one by one. You're doing it portfolio by portfolio. And so, what we've done at first stages, we've continued to, as the market has changed and merged as we've learned all this, is we brought more tools to the table. So, initially, we were just creating basically mounds of data. If you're analysts at the Federal Reserve Bank, they're fantastic analysts there. They can handle us just dumping our entire database on them. They can analyze it. They work their way through it. But if you're a smaller pension fund or something, you don't have that kind of horse power on staff that can handle that. And so, what we had created first read or the software tools to slice and dice the data organized by portfolio, do the cat modeling, do all the projections necessary to kind of give a very refined sense of what that risk is. So, it's a useful tool for them as they're making their decisions because they're making these decisions every day. That's great. Can you bring it to life for us? I mean, if I'm a client of First Street, what am I looking at? If I have a multi-tenant housing development that I'm looking at understanding the risk for, how do I interact with First Street's products? Yeah, so if it's an individual asset like that, you'd be looking at a map over where that asset is and you'd be able to see the spatial area around it and where the flood or the wind or the fire risk is. So, we show the pattern of what the hazard is around that property. And then you'd be looking at an analysis of what the intensity of each hazard is for that property. So, if it's flood, for example, maybe the projections will be two feet of flood there in a 100-year event. Then you would say, okay, if there's two feet of flood there, is it getting in the building or not? How high is the building? Maybe the building's already been raised up on piles or it's got some kind of retaining wall around it. So, two feet doesn't concern you. Or maybe you say, well, it's 20 feet and it does concern you. And I have to do something about this. I have to get some insurance or I have to do something to mitigate this physically at the site. It would give you the information you need to do that. We would also give an estimate of what that mitigation cost would be. So, you could do that return on investment. It's just going to be cost-effective for you to put this in. If you're going to hold it for 10 years, will you get your money back? So, we provide that kind of level of granularity in the decision-making too. So, if it's an individual property, we try to describe everything about that property, all the characteristics that we know about it. And of course, sometimes either the public records about that property may be incorrect or something for the satellite image of the property may not have captured something correctly. So, we give these are also the opportunity to go and change those parameters about the building. Maybe it's higher than we thought it was. It's elevated more. Or the roof type is different for wildfire risk or something like that. So, you can go and you can change those things too to make it correct. And then see what that does for your risk for that particular building. And then you can make your decisions about what you're going to do with it. Got it. So, that's for the individual. And then what about if you have a portfolio of thousands of properties? So, you would take those thousands of properties bringing it in an Excel file or a CSV file uploaded to our site. And once you've uploaded to our site, then we'll analyze each single property the same way we did that one statistically. And you may choose to look at any one of those thousands individually if you like. Then we roll those up into an aggregate risk. And what's important there is an exceedance loss curve so that you can look at for this group of properties. What are the chances are? So, you're looking at the probabilistically looking to the future for a one in a hundred year event or one in five hundred year event or one in twenty year event. What does that curve look like? What are the chances of you hitting a certain level of loss in that portfolio? So, it allows you to say, "Hey, maybe that my risk is too high and there's an uncertainty bound around that also too." Maybe most of that risk that you're not prepared for is coming from only a handful of properties within your thousand property collection in your portfolio. Maybe you decide to do something, divest yourself of those or mitigate those. Do something there, invest some money to fix the risk there. And watch your whole exceedance loss curve come down. And as long as it gets down to the point where it's manageable through either other risk transfer mechanisms or whichever you choose, then they give you that information, the confidence that you can proceed with your portfolio and be sure that the investment that you're making is going to be secure in the years at. Got it. It seems like another key stakeholder would be a home owner or a home buyer at the individual level. And it seems like there's winners and losers all over the place here. If the risks are revealed to be less than was generally thought, well, then you're maybe a winner. If the risks on the other hand are revealed to be higher than what was previously thought, then maybe you're a loser if you're the home owner or home buyer. Maybe you just want to know what is the risk. So I know if I want to invest a million dollars in this property and what's the risk profile look like. And if I have two properties that look otherwise similar, except for these risks, well, then maybe I'll buy the one that's less risky. What does that whole home buyer and home owner side look like? Yeah, it's been fascinating to see how this has evolved. When we first released the flood maps back in 2020, we were talking with a couple of the real estate sites, including realtor.com and redfin.com because they were in the same questions by studies that we've done at first street, Dr. Jeremy Porter has led a lot of these kind of metric studies and socioeconomic studies that yes, there is an impact on real estate prices. Sometimes you have to tease it out because other market forces are causing real estate to rise and fall. But if you look carefully, you can discern that things like flood risk do have a disproportionate impact on how that property, how its value is going to change over time and you have to look very closely. You can't just look at county level aggregates and stuff like that. So the eyes set them from Miami, Florida, if you look in Miami and this has been going on for 20 years. The markets have already been at work even before first street existed and it had scores on homes. People are already moving to the high ground. They're already leaving the low areas of Miami Beach. It's the old railroad track actually that old flagler railroad from way back when because that's the high ground. If you have an area that has got a lot of risk, it can really start to spiral down and we call them climate abandonment zones where people are leaving and prices are going down and it's not coming back. So the individual homeowner and counties and cities that collect tax dollars from real estate evaluations have a problem in the face. There are two kinds of people in the world. People who think about climate change and people who are doing something about it. On the zero podcast, we talk to both kinds of people. People you've heard of like Bill Gates. I'm looking at what the world has to do to get to zero. Not using climate as a moral crusade. And the creative minds you haven't heard of yet. It is serious stuff but never doom and gloom. I am Akshadrati. Listen to zero every Thursday from Bloomberg podcasts on Apple, Spotify or anywhere else you get your podcasts. Climate change isn't a distant threat. It's reshaping California right now. So what's happening? Who's impacted and what can we do about it? Sierra Club, California, in collaboration with stranded astronaut productions explores these questions and more in their monthly podcast, The Climate Dispatch. The climate Dispatch dives into the most pressing climate issues facing California, examining local stories, challenges and solutions, shaping communities across the state. From plastic waste and the housing crisis to climate migration, light pollution, and sea level rise, if it's happening in California, they're talking about it. Join host Tayyah Janet as she takes a deep dive into these topics, featuring insights from experts and uplifting the lived experiences, wins, and struggles of local communities. Listen to the Climate Dispatch at sc.org/climatedispatch or wherever you get your podcasts. I understand that you actually began to work with some of the real estate brokers and real estate agencies and do you think that there's a version of presenting climate risk that will work? I think so and I think right now and this has been born out by Zilla joint, Realtor and Redfin and Homes.com as one of our partners to release this information. And it was a highly publicized case for the holidays at the end of 2025 where Zilla took down the scores. They still had the passage of the first street site so people could still discover, but it wasn't so easily discovered. We had to do an extra click and this made the national news and such and that was born about because of this tension between the sellers and the buyers. It changes for provider to provider but getting this information out there one way the other is really the challenge. It's get it out there and let the in my opinion let the markets do what markets do and make those adjustments because government can't be in the situation of like picking winners and losers here and stuff like that but there has to be a level playing field that the consumers have the same information that the real estate folks have that the insurers have. Yeah it does bring up this question of which sector is going to be most effective in addressing this. There's lots of reason to think that this could be a private sector issue. Buyers and sellers are private actors usually. They'd have a demand for this information so you might imagine that that would just become part of a transaction due diligence process and we don't need the government necessarily or nonprofits but then there's all these market failures and they're differentially powerful and disinformation campaigns and all that so then maybe there's a role for nonprofits to come in and release maps and other sorts of information but then of course maybe there's a government role here and saying like an order for us to regulate transactions to make sure that externalities are properly accounted for we need to mandate the disclosure of this information and Connecticut is taking an interesting role here right. Connecticut's working with your data and trying to make that available to its residents. Yes exactly they have licensed our data in order to pass it on to the citizens of Connecticut so that they can start to understand what that risk profile looks like in their neighborhood at their home at their business and they're coordinating this across multiple government agencies also letting the business community understand this as well too so I clawed them for taking this step licensing the data is really the easy part of what their challenges right now their challenges communicating this risk across the states of people could understand like we were just talking about some people are going to be surprised by this at first and it's going to be a journey I think for a lot of the state but I think by moving early the sooner the state and its residents can prepare for this and its businesses can prepare for this and mitigate this risk there's a lot of things that can be done to reduce the impact of extreme events that are short occur. That's great so this really leads into some questions about capital markets and policy you're thinking about how the governments interact with different markets and with purchasers I mean you have some big institutions now like KKR and a number of other very large investors who are working with your data they're acting in different ways than consumers or individual businesses I'd love it if you could take us inside your view of the deal or due diligence or process so we talked about managing assets but I'm really interested in how investors are using your data and your models to constructive view of how they're going to go about sourcing deals that they might do how they're using it to figure out buy or don't buy and how they're thinking about managing those assets yeah when I've seen Guinness fascinating the diversity of views from different companies sometimes they have similar management practices but very different views on how they're going to address the risk across a portfolio and they all have different tolerances for that risk depending upon if they're acting on behalf of other clients or maybe like a pension fund they have some responsibility either to a government or to a company to some fiduciary responsibility to manage these things and the approaches that they take as they're assessing our data are there's some real similarities there so they usually have before they really dive in deep they'll have a subset of their portfolio that they are familiar with that they've already done some kind of due diligence on maybe they have some concerns about it for one reason or the other and it's basically like okay we'll show us what your tool tells us about these properties right and we're happy to do that and so we'll do these measurements and these assessments like I just described earlier and we'll sit down with them we'll go through it with them and explain what why things are being assessed the way that they are yeah usually can see the the light bulb go off in front of our tools you can just type in any address and you can see any location pop up and what most people do whether they're the CEO of a company or their analyst or whatever is it'll type in their home address and I've seen this a thousand times it'll type in their home address and most of us have a pretty good idea around our home address and our neighborhood particularly for flood what streets flood what corners flood during heavy rainstorm and that's the first thing that they'll do and they'll look at the five year or the 20 year return period and they'll go ah and you can see the light bulb go off like oh yes you are predicting where that would actually have oh okay and that opens the door to going in deeper and deeper onto the other apparel's also too but yes it's this combination of institutional assessment of a group and then also that individual human connection to a property or a house and then when they can look at the tool and they can understand that oh yeah this is resolving the kind of risk I would expect in that place I'm very familiar with and it opens the door to other investigations. It's really interesting you talked earlier about Fannie Mae and Freddie Mac and they're beginning to use your data this whole question of financial disclosure requirements as the ebbs and flows as different administrations change and so forth but I'm really interested in how this affects you as a firm trying to get your information out there does the fact that the moment changes how much emphasis there is on financial disclosure and risk disclosure does that make it easier or harder for you as you're trying to get this information out. In some ways in a very odd way makes it easier explain how so when there was a lot of the climate regulatory policy being implemented or discussed being implemented a couple years ago we did have a number of customers coming to us because they were worried about being in compliance with the regulation with those new disclosure laws so it was very much a compliance mindset I'm going to have to answer the mail I'm going to have to answer to the SEC or whoever I'm going to have to do my homework and understand the risk of my portfolio so I can explain it to the regulators so that was one personality type the other personality type is maybe driven by the kind of folks we were just discussing like a playoff pension fund with some responsibility to manage this risk over the long term so they can hit their targets for returns they have a different motivation right they're trying to make the most of what they've got and it doesn't matter what the regulatory landscape necessarily is but they know what they have to do in order to preserve their investment and so when you know change administrations happen a lot of executive orders that were around climate risk targeted at US Treasury or whatever those went away so a lot of that stuff got dropped the customers are coming to us for a more compliance viewpoint basically faded away a lot of banks throughout the US you saw a staff actually being like reassigned within the banks from the had you climate risk groups okay well we're not going to climate risk anymore you're going to go work someplace else in the bank or whatever so we saw a big deceleration on the compliance front but it opened up our bandwidth we're close about a hundred people now at first street and can it only engage with so many people at once but what it did opened our bandwidth to be talking with these other groups that had a different motivation and it's like we can go faster with them now and the strange way it's made it easier now that the regulation in the US has kind of set aside that momentum is gone the momentum is picking up now on the other side so that'll probably see saw back and forth I imagine over the next decades ahead but there's more than one reason to be motivated about doing something about climate risk that's for sure and are there parts of federal policy that are helping with your business and with your ability to get climate risk out there at this point you know I think there are some very positive signs and federal policy but some of them are coming out of FEMA which is not strictly financial FEMA being the federal emergency management association yes but they also do hazard mitigation and they also run the national flood insurance program and so we had talked earlier about some of the issues with the FEMA flood maps and how the average everyday American understands they have flood risk whether they're inside a FEMA flood zone or not right they don't have the full answer but FEMA to their credit now has just released their first flood map with Harris County where Houston Texas is that was hit by Harvey years ago the hurricane Harvey horrible flooding there they have now put out draft maps that include the heavy rainfall so this is a tremendous step forward for Americans being able to understand and be prepared for their flood risk in this country so kudos to FEMA for that it's going to take some years to implement this across the country of course it will take probably a decade or more my opinion probably to have this change percolate around the country and all the different assessments and modeling that needs to be done but you know we'll get there on the financial side I don't think there's been any federal policies that have come out that have helped us quite frankly but there hasn't been any that have hurt us either so in the previous administration there was an executive order to assess the climate risk on the health of the banking system and the financial system now with the change of administrations that executive order was rescinded so there was some movement pending at the SEC the Security Exchange Commission requiring companies biting beyond the banking sector to reveal climate risks and that's been put on pause or maybe cancel it all together would that have helped drive demand for the information that you and your competitors are providing yeah it probably would have again from the compliance standpoint they would have brought more people from the compliance viewpoint forward whether that would actually solve the problem that we have as a nation addressing climate change it might help some it's created room for other players in this space that have different motivations than that the other thing is that the stockholders in these companies have also woken up to this reality also too and so they may not be labeling it as climate risk but it's fine to a home within the risk management structures within companies. The idea of materiality, the fact that this can be quantified now because of the tools at first street and other vendors and climate services space have produced really encourages I think investors to demand. They want to know how is this impacting things. And I think as time goes on, even things like municipal bonds, which were always considered, oh, this is a safe haven, this is a sure thing. It's like, well, no, a lot of these projects are in some risky areas. And what is the climate risk for that project that's being paid for by that muni bond? Is that a good investment as we think it is, right? So these questions are being asked now. It may not just be a requirement from the government, but it's just good business. So investors are going to be careful with their money and this information. Now that it's noble, the climate risk is noble or more than one source, I think the ball is really rolling down. When we first started talking, you mentioned that when you joined first street, it was a non-profit. Now it really sits at the intersection of being a commercial business and being a public good. I mean, you're even a public benefit corporation. Can you describe what that is? What is a public benefit corporation? How do you think about this role sitting at the intersection of these two very important parts of climate change? Yeah, it was very interesting to see this evolution of first street from a non-profit trying to figure out how do we communicate about climate change? It's like, oh, I think we understand where we can actually do a lot of good for industry and for this country by going down this road. And it was sometime probably in the middle of 2023 that it dawned on us that this was the change that was happening. And because we were licensing this data, we were creating two different companies and different government agencies in different states, really seeing the uptake of the use. The revenue that was coming in, we were going to be breaking even so our donors were very excited about this. They're like, this is fantastic. One of the reasons I came to first street too is a data nerd. I was also very interested to see if we could create and maintain data based upon its value to industry and not take any government grants, not take any of those public funds that usually research is based on, but can we pay for itself? And the answer is yes. And then the donors said, well, now you've also proven there's a market for this. And non-profits exist to fill a need, where for-profits aren't going to do it or governments don't want to do it either way, but there's a niche there that non-profits fit nicely into. But we had shown that this niche we were in is actually that are fit for-for-profit. So yeah, we spun out as a for-profit. We kept our public vision with the public benefit company that yes, we are doing a public good. We're creating data that are useful for the greater good of our society and our businesses. If this is going to help propel good decisions that mean a safer society for US businesses and US citizens and fantastic. It's a very fun job to have, but now also too, then as that market is maturing to see as our journey now we're a little over two years into the for-profit journey here. And we're seeing the markets continue to increase in size and increase in skill. And they want more different types of data and more sophisticated data. It's great to see this evolution from like how do we tell the story to like oh the story is landing and they want more. They want more detail. A finer grained response on those financial impacts is like yeah, and we can do that. So it's been a very fun journey. Great. Well look Ed, we've covered a ton of ground. The final question I ask of our guests is to give advice on resources that listeners who are interested in learning more can consult in order to actually dig in whether that be websites or podcasts or conferences or newsletters or books or reports. What would you suggest or some top resources that such folks could go consult? Yeah, there's some wonderful government resources both at the National Ocean and Gaatmysphere Administration NOAA as well as NASA as well as the USGS, US Geological Survey EPA. There are some wonderful data sources there that really describe the basics of climate in a very useful way. Then when you've got companies like First Street we put out a lot of reports because we take our data and we apply them to certain questions whether it's real estate or insurance or whatever. We usually have webinars that go along with them too but they describe our data applied to that particular subject of interest. And so you see quite a few of those types of things out there too. The insurance industry and re-insurance industry put out a number of annual reports that look at usually with a global kind of coverage, global kind of lens. Showing how extreme events are impacting their bottom line, their customers and it's very eye-opening when you start to look across, get away from the climate service vendors like First Street, you go to more of a general risk group like a re-insurance company and you look to see how those risks from extreme weather events now are as big or bigger than anything else that they're worried about. Climate risk is not an niche stuff. It is the subject across risk management now, physical risk management and so it's very interesting. I encourage your listeners to seek out some of these big multinational like immunic re or somebody like that. Go check out some of those reports, they're public and they describe the situation well and watch out for those graphs with a lot of graphs showing increasing losses over time, whether it's from severe convective storms and hail which cut everybody surprised by last year. It's all good, great. Well thank you so much Ed first for spending time with us. Yeah thank you, pleasure being here. That was our conversation with Ed Kerns, Chief Science Officer at First Street thanks to my HBS colleague John Mulligan for co-hosting today's episode. You've been listening to Climate Rising. I'm your host Mike Tauful, Sophie Wong produced today's episode. Craig McDonald is our audio engineer. We'll be back in two weeks with another episode of Climate Rising. See you then.