Startup Series: Cloud to Street
Today's guests are Bessie Schwarz, Co-Founder & CEO, and Beth Tellman, Co-Founder & Chief Science Officer, at Cloud to Street.
Bessie and Beth met as Master's students at Yale University's School of Environmental Sciences and Forestry, where Cloud to Street started as their thesis research. The company is the world's leading remote flood mapping platform. Cloud to Street uses global satellites and remote sensing AI to monitor flood risk and detect worldwide floods in real-time. Its unique technology requires zero ground equipment and provides governments and communities with accurate and trustworthy flood monitoring. Seeded by Google, Cloud to Street provides disaster relief support and data to governments in almost 20 countries worldwide. Partnering with top insurers, the startup is launching the first commercial parametric flood insurance product to protect climate-vulnerable communities better.
Bessie and Beth are great guests, and I was looking forward to having them on the show. The two co-founders explain how Cloud to Street came to be, what sets the company apart from other flood monitoring businesses, and how their product works. We also discuss how natural hazards, blue lining, and climate change negatively affect frontline communities and how Cloud to Street can help.
Enjoy the show!
You can find me on Twitter @jjacobs22 or @mcjpod and email at info@myclimatejourney.co, where I encourage you to share your feedback on episodes and suggestions for future topics or guests.
Episode recorded August 2, 2021
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Jason Jacobs: Hey everyone, Jason, here I am. The my climate journey show host. Before we get going, I wanted to take a minute and tell you about the, my climate journey or MCJ as we call it. Membership option membership came to be because there were a bunch of people that were listening to the show. That weren't just looking for education, but they were longing for a peer group as well. So we set up a slack community for those people. That's now mushroomed into more than 1300 members. There is an application to become a member. It's not an exclusive thing. There's four criteria. We screen for, Determination to tackle the problem of climate change ambition to work on the most impactful solution areas, optimism that we can make a dent, and we're not wasting your time for trying and a collaborative spirit beyond that.
The more diversity, the better there's a bunch of great things that have come out of that community. A number of founding teams that have met in there, a number of nonprofits that have been established, a bunch of hiring that's been done. A bunch of companies that have raised capital in there, a bunch of funds that have gotten limited partners or investors for their funds in there, as well as a bunch of events and programming by members and for members and some open source projects that are getting actively worked on that hatched in there as well. At any rate, if you wanna learn more, you can go to myclimatejourney.co the website and click. the become a member tab at the top. Enjoy. the show. Hello everyone. This is Jason Jacobs. And welcome to my climate journey. This show follows my journey to interview a wide range of guests to better understand and make sense of the formidable problem of climate change and try to figure out how people like you and I can help.
Today's guests are Bessie, Schwarz, co founder and CEO. And Dr. Beth Tellman co-founder and chief science officer of cloud to Street. Cloud to street uses satellite and AI to track floods in near real time, anywhere on earth to insure risk and save lives. We have a great discussion in this episode. about Flooding the magnitude of the problem, how the problem has been evolving, the role of climate change in accelerating that some of the existing flood models, what they do well and where the gaps are, who's impacted by those gaps.
And then we talk about the cloud, to street solution, what they do, how it's different than existing flood models. How it's better and who it's for and how it helps governments and how it helps insurance companies to make sure that everyone has the coverage they need and their risk protected so that they won't be left without a home, without a business, etc. Bessie, Beth, welcome to the show.
Dr. Beth Tellman: Thanks. Great to be here.
Bessie Schwarz: Thanks for having us
Jason Jacobs: I'm psyched to have you, As, as you both know, we're big fans of cloud to street here at my climate journey and really excited for the chance to learn more about it and enable listeners to do the same.
Bessie Schwarz: Yeah. Well, we're big fans of the podcast too, and you've had some folks we really look up to on this podcast before. So, Excited.
Jason Jacobs: Awesome. I'm sure there'll be many people that are saying that about you [
Bessie Schwarz: laughs].
Dr. Beth Tellman: [laughs].
Jason Jacobs: ...as well. So
Bessie Schwarz: or the opposite? [
Jason Jacobs: laughs] So take it from the top, what is Cloud tom Street?
Bessie Schwarz: Yeah. So cloud to street is a global flood risk platform that uses AI satellites and other forms of new data, like local intelligence in order to track floods in near real time, like the kinds of floods we saw in Germany and China, and even in Arizona where Beth just moved and also uses the same types of data to analyze risk remotely anywhere.
On earth without any ground data and this new way of doing flood analytics from the cloud to the street, as opposed to the reverse enables us to fill really critical information gaps around the world. It's been used now by 18. Primarily national governments and some of the hardest hit places around the world, like the Republic of the Congo India. And now we are collaborating with global insurers and reinsurers in order to build a financial safety net for everybody around climate risk.
Jason Jacobs: Amazing. And maybe talk a bit about the origin story of the company, but also would be great to hear a bit about each of your origin stories and how you came to be doing the work that you're doing. So take those in any order. that you like.
Bessie Schwarz: Yeah. I actually love answering [laughs] those questions together in part because Cloud to Street really does come from the perspectives that Beth and I both had on the ground with communities. And so we can answer those together and in both of our stories first. So Beth and I actually really neither of us. And it's really in our work together. Even before Cloud to street intended to start a business, we really intended to solve particular problems that we've seen at the local level. My background is as a community organizer. Working in the US and always on climate change and that's background, she can share in just a second is as a disaster relief worker.
And really ironically, I think we came to somewhat similar conclusions in the couple of years. We worked on the ground before we met each other. So in my work as an organizer, I've worked with communities that were affected by climate change all over this country. So I started my career working with young people in coastal Florida who were primarily looking at having to leave where their family had been for generations.
And in some cases I've worked with low income communities in the Midwest who were hit hard by. Floods other kinds of climate impact. And then we're not being captured in the new policies we saw with a transition to a clean energy economy. And I found as an organizer, I could have a really big impact at a local level by helping people realize their own agency within a system and organizers perspective to problems is to look not just at. What someone's current situation is like someone who's our community. That's not having their needs or rights met and asked not just like, what do they need now, but what is the system of power around that person such that they're not getting their needs or rights met, it's a systems problem, and then helps in the same way, lean into a solution.
That enables those people to understand their agency within that system, whether that's political, cultural, whatever, if they come together as a collective and kind of rebalance that power sustainably. And so I did that was very proud to do that. A lot of local levels, many people I worked with became political for the first time, but that I realized after a couple of years was not gonna scale to the speed of climate change.
And so I went back to grad school where I met Beth. Literally day one of orientation, Beth had this, [laughing] it was like, Beth's purple backpack with sparkles on it. That became kind of famous at our grad school. And I was like, okay, I guess I'll be friends with that person. That's the types of stuff like data you use day one to decide you're gonna become friends with. And we started a conversation. We became roommates because of the purple backpack. Namely, we started a conversation about what lack of data meant for people who are trying to protect themselves in the face of disasters and other kinds of climate risks. And Beth kind of like was [laughing] coming from a different perspective, but came to a similar conclusion. Do you wanna share that story Beth?
Dr. Beth Tellman: Yeah. So for me, I was actually doing flood and landslide relief in El Salvador, before I met Bessie, I lived there for four years and. Started my own nonprofit to respond to hurricane Ida in 2009 in the communities that I was supposed to do coffee farming research in, but I stopped doing coffee, farming research when major flood.
had Devastated the communities I was working in, and that was much more important to [laughing] attend to than the coffee farming research I'd proposed to do for my fall right there. So I ended up raising some money and supporting community leaders and relief and response and recovery efforts. And. Ended up getting really involved in staying there long term and starting a nonprofit because all the issues that I saw and the flood recovery and relief process, the communities I was working and we're not getting sufficient aid because the local government that they lived in was really corrupt and had intentionally left the names of these communities off the world food program aid list, because those communities weren't voting for that Mayor who is in power. And so I kind of saw how lack of access to transparent information about who's affected and where was unfortunately allowing corruption and political manipulation to drive, who gets to recover and who doesn't get to recover from floods. And so I started working with communities there and the nonprofit I founded, which was great, and doing community organizing and rebuilding communities together.
But eventually. wanted to search for something bigger. I found that, you know, people had questions like, oh, can we plant some trees on this hillside and will it prevent the flood? And we didn't really know the answer to that question. And so I went back to graduate school to really learn the science of flooding and think about how I could drive more.
Data and analytics into decision making around flood mitigation. And that's where I met Bessie at the Yale school of forestry. And that's where I learned about satellite image analysis and remote sensing. And it sort of dawned on me then, "Oh, wait, There's technology that can make flood maps and transparent information, not just for the three communities I worked in El Salvador, but this can be done globally.
And so as I started to learn flood mapping science, it became quickly apparent that the class projects that Betsy and I were working on had a really, really large impact on utility, outside the classroom so much so that people started offering us contracts and money to run our initial models. First happened in New York, and then it happened in India. And it was like, okay, I guess there's a real there here. And how are we going to leverage the impact of this science? We've got to start an organization. So we ended up applying for some Google research money to work on our model. And that was kind of the first real seed grant that cloud to street received. And it's really grown from there. So, you know, in a lot of ways I feel like cloud to street chose us. We didn't intentionally start the organization in some ways. you know.
Jason Jacobs: And so, as you were working on these models and people started showing up and wanting to pay you, what were the initial use cases that first came about?
Bessie Schwarz: Yeah. I mean, we really did start it with the idea of Beth's experience and El Salvador in mind. Like, I, I remember very distinctly Beth talking about like access to quality information. And so it was a pretty kind of meta and global idea as Beth sort of mentioned here, we ended up going out to mountain view, [laughs] or just started Cloud to street before we really knew How to code as we're taught ourselves that over the summer, after Google came and presented a really early version of their satellite analytics platform. And then we flew to mountain view that summer to present a really early version of it. And then they got pretty jazzed about it and ended up helping us go to some conferences and some user headquarters in order to validate it.
And that's sort of said, we presented what was really possible through now the level of. Planetary scale analytics, the cloud computing was enabling us to do, and we just had users coming up to us saying we don't have access to high quality information that we need primarily in the developing world in order to do in some cases major, Major investments. So just one of the biggest examples first was in Northern India where we met someone at the headquarters of the world bank, who said that the previous year, about 5,000 people had died in a single flood event there. And they didn't have new flood maps in order to make what was a hundreds of 1000s of million dollar loan to the area.
And what they were doing was contracting a very good and large engineering company to put round equipment all through the watershed rerun hydrodynamic models to figure out where the flood risk was after this major event. and it was a very good and well developed science, but it would take years and a lot of expense in order to get that information.
And so they needed to fill the information. Gap much more quickly for the state in India as they were starting to recover. And so that was one of the first projects where Beth and I thought, okay, we have to, we weren't intending to do this or come in and solve exactly this problem for large agencies and development banks, but the need is clearly so there. And I always like telling that story because in many ways we're doing very similar things now in about 18 countries. Some of the use cases are a little bit different since that time.
Jason Jacobs: And once you had the realization that having this real time global data using satellites and AI, without needing to put this equipment on the ground in a way that faster and less expensive than what existed previously did you immediately jump to for a profit company, or was there some debate, did you evaluate different paths? How did that come to be that you're building a, a high growth startup?
Bessie Schwarz: Yeah, that's a great question 'cause we definitely did not jump there immediately. I mean, Beth and my road to where we are today, I'd say was very, I mean, thoughtful. is like a euphemism for slow and really testing things out. So we originally, this was a Research idea. And we thought this should live in the world and we didn't really expect anyone to start paying us at least this quickly. And while we have had customers and revenue since really day one, the reality or the kind of hidden truth is that we had customers and funding from Google before we realized through Beth's dad's friend that we actually had to start a company because we couldn't just take all that money into our personal bank accounts.
We're like, okay. well, We'll start that in order to take in the money and keep going here, but we really toyed around with a lot of different avenues for creating the kind of solution we wanted to and entertain the idea of becoming a nonprofit for a long time or sticking just mostly on the research and data production side of things. And Beth and I, in the beginning, were really focused on proving that this new type of science really was high quality and scientific rigor has been one of our core values that Cloud to street since then. So really developing out that this was reliable enough for long term decision making and we didn't wanna just fill the gap with something that looks fancy.
And then the second thing we really wanted to prove was impact before we decided to scale. At a higher revenue, and we're really proud that we're there today. And we tried out a couple of different models and it really was, I'd say only about 2018 when we feel like. we Hit the goal of having at least one community that we could very clearly identify and track very specifically our data to impact that we decided like, okay, now we feel comfortable with scaling. And we actually only just raised our first proper venture capital round a couple of months ago in order to scale.
Jason Jacobs: Uh-huh [affirmative]. And when you prove things out with that one community, maybe talk a little bit about what you proved out and the solution that you actually provided. them.
Bessie Schwarz: Yeah, certainly Beth, you wanna jump in on that one?
Dr. Beth Tellman: Yeah. I can take that one. At least I can give you kind of the story from a technical perspective and Bessie can maybe add a little bit more, cause she kind of had the initial direct interaction with the client. So one of her first near real time flood monitoring systems that we built and tested was at the world food program with the Republic of Congo and with the government there and.
What we had done when we built that system was kinda this is the typical cloud to street product, a much more evolved version of it today, but adjusting, all possible public satellites, running flood maps and monitoring where flooding is happening anywhere in the country. Very important for somewhere like Republic of Congo, which has only three stream gauge on the ground stations in the entire country. And the last time they had a big event, it took three weeks to get food aid to the community that needed it, because that's how long it took to confirm who was affected, where, what was the magnitude and get all the approval. So our goal was really let's get that from three weeks to, you know, days or potentially even hours So we built this system. And while we were monitoring the Republic of Congo, they had a situation where four refugee camps from the democratic Republic of Congo on the other side of the Congo river had moved into a Republic of Congo Brazzaville. So the country, just on the other side that we were working in.
And the world food program wanted to know, are these refugee camps at flood risk? Do they need to be relocated? Can you give us some information here? And we were quickly able to, within a matter of a few days, do a flood risk assessment for each community found that there was one community that had flooded three times in the past 30 years And that kind of Land area. And in fact, we could even see with high resolution commercial imagery from the satellite plant scope that it was starting to flood now. So they took that information, made a recommendation to the government that they consider relocating this refugee camp. And were able on the basis of that.
Transparent information able to make that recommendation decision. And the government said that it was kind of dispositive, that they wouldn't have been able to make that decision otherwise and how great it was to have access to data, to confidently show that decision that really ended up mattering because one year after that recommendation was relocated.
That same community flooded again and there could have been, I think that refugee camp had about 7,000 people living in it. There could have been an impact of up to 7,000 people whose communities or potentially lives had been affected. And we were able to help prevent some real impact in that community. So that was proved to us. that Historic satellite analytics and understanding risk matter near real time, information matters. And going back to the stories that I talked about in El Salvador, that kind of data transparency that you can get from satellite data can be this really helpful boundary object and potentially, you know, shielding potential bias or or some political issues that might exist and can enable a quick decision. So that was a big proof point for us.
Jason Jacobs: And when was that?
Dr. Beth Tellman: It was [laughs] so interestingly enough, from a company perspective. So it was like very, very early 2019 when the, the refugees and asylum seekers moved from the DRC to the RSC, late 2018. I essentially [laughs] got a text message or like a mobile from the flood response group. We were supporting.
In the country at the very, very end of 2018 and then 2019, they were relocated. And what I find interesting is the cloud to street sort of history is that in 2018, our top company priority, was not revenue was not a product. It was impact one community. wasn't even a large like impact number.
It was like, we want to be able to identify kind of, without a doubt to ourselves, we can. help Seriously, a number of people whose lives would be much worse without us. And we were very open about like what that would look like. And we had a really hard conversation with the team at the end of 2018. I was like, We don't think we can name those committees."
We've been at that point, monitoring millions of people who are at flood risk. we've been supporting a lot of governments. I think it was up to a dozen governments, usually the national who are using the system, but we're like, we cannot trace where we go from our data to a user To a beneficiary whose life is seriously different and we can, we can show it's possible.
It happened, but we couldn't identify it. So we weren't satisfied. We had a really hard conversation with the team, we're like, let's take a hard look at this and you know, whether or not we really are convinced we can have serious impact when we go to scale. And then [laughs] just ironically, like a week into 2019, we're like, oh actually, no, we have proved it to ourselves. And so we got, that's why I remember exactly what it was 'cause of that hard conversation.
Jason Jacobs: And once you got that learning, what did that mean as you set up the scale and then maybe just walk us through a snapshot of what transpired over the last couple of years, since that. moment?
Bessie Schwarz: Yeah, we've had a couple of really strong realizations. And I just say one of them that I think that story really showcases is the value of really working with communities and with users for a long period of time before disaster strikes. I think we do see in our space, like by the time you're responding to a crisis and you're in an emergency, it's very hard to come in and, and make a different kind of change. And then in the recovery phase, you really can. But we really like to look at the risk that's out there now. And partner with organizations primarily with governments and now insurers who are providing capital Well ahead of time in order to be there when they have the text message. So about the time that UN, texted us, they were familiar with the data.
The government knew our name. we've been working with the government officials and the UN for UN kinda community in the local area for months at that point. So it really was just in the end one real analytic. Like they didn't even want a map. Really. They just wanted to know. Which of these companies at risk? How confident are you and how bad? And it was almost like just text messages then, now with some maps that had some methods that they may or may not have really read deeply into. Um, but it was the level of kind of like trust and understanding that we built beforehand that enabled just that quick text message to meet their question and answer at that moment.
So at that point kind of armed with the learning of not just What is the data, but what is the capacity building and the user support that we need to do to enable impact? We basically decided to try to productize as much of that support as possible over the course of 2019. So interestingly enough, that year we actually scaled back the number of governments that we were supporting in order to go deeper in the Republic of the Congo.
we're now we've Been proud to work for a number of years, Ghana and a couple of other places over the course of that year. And then in 2020 and 2021, we've scaled back up. So we're in a number of different governments now, but with a much more comprehensive approach through the product and through our customer support team, the other major learning, I'd say, as we really started to enable more decision making at the national government Level with some of the countries that I've mentioned is that we would actually consistently hear from the government's, Hey, the state is all great. but, If we don't actually have the resources to take these new types of decisions to respond to more people who are at risk relocate communities put in protection infrastructure, we don't have the actual resources to do that.
It doesn't really matter. So you can go ahead and tell us which communities are at risk and even, that, No, this factory is under water now, but if we don't actually have access to disaster capital, we're not gonna do anything differently. And we will struggle to do something differently. They do an amazing amount with low resources.
And at the same time, we had some of the largest insurers, reinsurance brokers around the world coming to us to say, Hey, we actually use the exact same product? You have the exact same near eal time and risk analytics to underwrite to try to release. Disaster capital and different types of risk transfer to the same places you're working where the interest just haven't been able to access because of data availability and some other things.
And so that was the other big realization that there was this real need and gap that we saw within the resilience process, but actually a real desire by insurance and capital markets to support that if we can make the mechanisms. work Effectively and equitably. And so that's really what we've been pushing into over the course of 2021. So doesn't expanding the number of places we're working with, a more comprehensive approach we're now actually offering through the insurance partners. We have disaster capital and different forms of. insurance.
Jason Jacobs: And for these insurance providers, what was motivating them to try to crack this nut and pursue this market? was it out of the goodness of their heart? Or was there some financial? [crosstalk 00:25:00]-
Bessie Schwarz: [laughs]. Yeah, I mean, I would say that insurers are deeply concerned about climate change and climate resilience, but you know, I don't know deep to severe heart. I think the fact the matter is that everyone's looking at the, What's called the protection gap. The fact that 70% of disaster losses around the world are uninsured. And for many purposes then unprotected, this is not only. a Huge problem. As we try to survive climate change. And by the way, flooding is 50% of all hazards, natural hazards. It is a huge missed opportunity from the markets perspective.
And we just have not been able to make a serious. Crack at that margin at the 70% gap for a long time. And so we knew, and the insurers knew that we'd have to try something in a different way just to take advantage of that, of that opportunity. Beth can probably talk a little bit more about, [laughs] about that too. And about some of the kind of local examples.
Dr. Beth Tellman: Yeah, I would say some of the motivation, I think for insurers to try something new is that the traditional approaches weren't really working to fill the protection gap, the traditional way of mapping, who is that risk. And then identifying when a flood happens in near real time is by using a flood model.
So. Building a big computer model of where water goes on the surface of. the earth. And that might work well, if you have a lot of equipment on the ground, as we talked about but you can calibrate that model too. But let's think about the example we've talked about at the beginning, the Republic of Congo.
Three stations in the entire country. That's simply not enough data to calibrate a good flood model. So it's gonna be pretty tough to write an insurance policy there with a low enough uncertainty that you could really get a return on the investment as an insurer, or even feel confident building a product and making a sale there.
So this is where satellites really come in, because you can see where the. water went with pretty high certainty. You can even look historically and see not where, what a model predict that the floodwater goes, but where did it actually go? Do we have levees built here? Has the irrigation system changed? How are humans changing the surface of the earth in a way that changes where water goes, how risk is changing and how you wanna price your insurance policy?
So the technology that we had built was really perfect for. Potentially being a solution to actually being able to get the data that insurers would need to underwrite and sell a policy and to develop a new type of insurance. That's based on this data stream called parametric insurance. and on our best if you wanna go, go deeper into why, why satellites enable this new type of insurance and how it's different from the traditional flavor.
Bessie Schwarz: Yeah, I mean, Beth and I could really go on and on for this topic together for a while, but one thing I just wanted to say is that we're talking about really important and fairly extreme examples, like the Republic of the Congo with three stream gauges. And this happens all over, especially the developing world, but in the US, which is.
the Best gauged country in the world has major gaps in insurance and access to flood information here. And from an insurance perspective, we talked about insurers all the time who say, you know, unless you're sitting right next to that stream gauge. And even if you are sitting there, if the flood is too great.
That essentially goes like over the head or over the top of the stream gauge you can't insure it more dynamically. You can insure it through what's called a parametric. Method. And so there is just big amounts of there's huge, huge gaps in this country. From the existing insurance, we have very complicated public insurance scheme here called the NFIP, that leaves a lot of people and a lot of businesses at risk.
And a lot of insurers are trying to look at other ways that you can add supplemental insurance. or Absorb other types of pockets of risk that aren't met. And just even the incredible amount of gauges that we have a really impressive amount here is just not gonna be sufficient to do that. And it also are really, really eager to help absorb that amount of risk.
And frankly, I talked to a lot of them, like to are just really scared about the risk that they're very aware exists from flood risk in this country.
Jason Jacobs: So going back to something you said about the equipment, and it sounds like. One benefit to the cloud to street solution is that it opens up the ability to insure to places where this Equipment is not prevalent. One question I have is how prevalent is this equipment? And then a follow up question is in the areas where it's already prevalent, how does the cloud to street solution compare. Is it just meant for places where the equipment is not? Or does it have a value proposition in the places where the equipment is today?
Bessie Schwarz: Yeah. Beth can definitely talk about the availability of equipment just so good.
Dr. Beth Tellman: Yeah. So I'll tell you what we know, And a little bit of what we haven't yet quantified. So we actually did do a comparison in four different watersheds in Sub Saharan Africa that we published in a peer reviewed scientific journal comparing A flood model to the cloud, to street approach of using satellites to estimate flood frequency. And what we found there was that in the sort of more frequent type of flooding, we're talking here up to about the 50 year return period. So this would be your sort of, if you're not familiar with return periods is kind of.
Moderate risk type of situation that satellites perform much better than models models don't do well at predicting the floods that tend to happen every two or 10 or 20 years, satellites are much better. We published that study and we can send you. The link and environmental research letters in terms of, we haven't done the same comparison somewhere like the US which has 1000s and 1000s of strain gauges.
But even in that case, there are a lot of examples where a flood model is not even set up to predict the kind of flooding we see with satellites Lemme give you one example, dam breaks and ice jam. So. hydrologist call these random or stochastic events, things that happen that you can't really build into a model.
So in 2009 in Fargo, North Dakota, there was an unprecedented amount of rainfall on the red river, just after winter. And it started breaking up all of the snow and ice and blocking and jamming the river and got an enormous flooding like way, way, way outside. The FEMA floodplain, that we could see by satellite, but that a model would never have predicted.
So there are so many types of events that even in a well instrumented location where maybe a flood model would do well in the US that satellites are gonna give you a better picture of the event. The dam breaks in Michigan, actually in May, 2020. If you heard about that. event. We could see a lot of detail and where the water and the damage was by satellite in a way that a flood model wouldn't have been able to predict. So those are kind of two examples that can stay even in highly instrumented areas.
Jason Jacobs: And it sounds like you're customers with the satellite solution uh, governments and insurance providers are the flood maps. Do they have a set of vendors essentially providing flood maps to governments and insurance providers? And should we think about cloud to street as uh, competition and, or a potential replacement for flood maps, the new and improved version, or is it different? than that?
Dr. Beth Tellman: So there's a lot of ways and that they're complimentary, there are actually things that flood models can do that satellites cannot. do. One is future predictions and climate change.
So, because we work with satellites, we see the past and the present, we do not see the future. So what is actually really important is to use a flood model, to understand how overs change under this climate. There are some places. that Satellites. Can't see very well and really dense urban areas or in flash floods where the water moves very quickly.
Sometimes we don't get a full view. and So actually combining a model with satellites, could give you the best possible solution to understand your past present and future risks. So we can replace a lot of what models do. But there are a lot of functions where I actually think there's complementarity between the two.
Bessie Schwarz: Yeah, exactly. We very much see ourselves as one of the important new solutions, but it's really one of a toolbox that a community, a government, or even in some cases, an insurer needs in order to offer what they need to in order to protect the community or to insure the assets and the people that they are.
So we have identified a really critical information gap. that is Exactly suited to this new type of technology that really Beth has pioneered as our chief science officer, but we always encourage folks to use it in concert with other things. And we're often finding ourselves, bringing in folks who run more traditional models into projects with our customers and kind of sub contracting to fill those longer return periods that Beth was talking about.
here. And it's really an kind of all different types of solutions. And we're also really excited about other types of new technology to be brought to the, the flood risk space.
Dr. Beth Tellman: And maybe one last thing I'll I'll add in because this is a pretty big achievement for us. And I think illustration of the whole, story we're trying to tell about the differences between satellite and models is that we just recently did a study of flooding around the world and built a database of 913 large floods.
It's called the global flood database. It is on the cover of nature for. August 5. And the reason it's the cover story and able to be published in a scientific journal of that caliber is because what we found when we looked at the change in flood risk and the proportion of population exposed to floods with our satellite data.
Is that it's 10 times higher than if you measure that same factor with flood models. And so it's actually giving you fundamentally new scientific information that helps us understand the phenomena of floods in a different way, not just for decision makers, but even for scientists. And so please check out the global flood database.
It's public re-available to download online. And the nature paper is in the August 5 edition.
Jason Jacobs: that's amazing. And going back to the flood databases, so who is providing those to the governments and the insurance companies, is there a set of vendors and what's the business model for those, and then same question for cloud to street. What's the business model. And is it coming out of the same budgets and the same decision makers as the flood model providers? Or is it a, is it a different pool of. capital?
Dr. Beth Tellman: Yeah. So a couple questions in there. remind me if I've forgotten one of them.
Jason Jacobs: I always ask them in twos. I don't know why, but yeah.
Bessie Schwarz: Yeah. Or threes or fours.
Jason Jacobs: Yeah. [laughs].
Bessie Schwarz: The [laughs] ...Yeah. So the way that almost all flood insurance or catastrophe insurance works today is you'll take a flood model or a hurricane catastrophe model. You'll run a bunch of different scenarios. It's a physically based model. simulate Future probability in a particular location, come up with some number of risks for your factory, for this particular neighborhood.
For this home. It has a lot of inaccuracies. If you don't have really, really high quality local data, and that's what Beth was alluding to before, it also has a lot of inaccuracies. If you don't think about how risk is changing due to climate change and population migration, which is actually. a Huge finding from the, the nature paper that that just read. So you do that come up with a number. The thing about insurance is that they don't actually mind if there's a level of uncertainty in the model, as long as they can quantify that uncertainty and place a bet on top because insurance is basically gambling. So you get that. And then when the actual event hits you, send someone with a clipboard in the case of insurance to go centrally assess How damaged your front porches or how damaged the equipment was at your factory or your farm or something like that, that process can take weeks. It can take even months and then can be held up in disputes or litigation. Instead of doing both of those processes, we can actually just analyze both. the underlying Risk or large portion of it and the actual damage to that portrait, or at least the exposure to that porch all remotely through our technology and then pay it out in some cases almost instantaneously.
So we just say, Hey, you don't need to wait for that clipboard person to go check it out and then fight with them about how damaged the porch was. We can show you in this satellite image. That your porch and, you know, everybody else within the area, or even the state have been impacted and then do that payout right there in a very transparent open way.
So the first thing there is a real industry that I think has some as well developed has some issues, especially with incorporating climate models into it, but a well developed industry around catastrophe modeling and flood modeling That insurers all use. And there are some companies that we really respect too, who do that work, but there's massive amounts of gaps and issues in it.
So we are offering in some cases, a better product, in some cases, a complimentary product for that, when it comes to the payout process, that's the clipboard person. This is a totally different way. Of doing your payout. And it's frankly, one that the insurance industry has been talking about as an innovative new approach for quite a while at this point, and actually has worked in some cases for things like droughts and others that are a bit easier to use satellites or other types of instruments for it, essentially doesn't exist for flooding, which again is half of all hazards because of a a quality and gaps within the data. And that's what our technology solves. So we offer a totally different way of doing that payout within a parametric insurance model
Jason Jacobs: So, for the planning and catastrophe aversion. It's essentially you can do it better either in addition to, or instead of, and then for the insurance it's we can enable this new type of insurance that you can't deliver without us.
Bessie Schwarz: Yep, basically.
Jason Jacobs: And how are you staging and phasing things as you take it to market Is there? One of those that is the bigger priority, did you start in one and you're expanding to the other? Where are you today and and where do you expect to be? If you look over the next, say 12 or 24. months?
Bessie Schwarz: Yeah. So, I mean, today we are leaning in even more to the support we're providing to governments with a real focus in some of the most vulnerable around the world.
So today we monitor about 122 million people with the technology and support, primarily governments, but also aid agencies and more local stakeholders to provide disaster relief, other types of response. We wanna expand that greatly. We work quite a bit with the world food program at the global level, to make sure that the entire developing world can be covered by this kind of information.
or at least have some basic level of data and ability to respond faster than as Beth pointed out the three weeks that it took the Republic of Congo to know that 1000s of people were without food. So we wanna take that to the entire developing world and then expand to really fill gaps that governments in the us and other developed parts of the world have.
We are also right now working with a couple of very closely with a handful of insurers and global brokers that I don't think we can share yet publicly in order to enable them to also bring exactly the kind of product I just mentioned to you to a variety of different places around the world. So the same exact governments that we work with to support the disaster preparation and analytic side, The same places that have said to us, we actually need resources to take these decisions now that we have the data and we trust you, we need the resources. So we're working actively with those same places to bring them in mostly as a way to insure the entire government through what's called disaster excess loss when they experience kinda their own version.
of Hurricane Katrina, they can get a payout. We are also working on doing this in creative ways in, [laughs] ...I won't say too much, but hopefully can soon in the developed world. And we hope to expand that to cover well over 10 million people in the next year through this kind of disaster insurance protection.
Jason Jacobs: And one question I've got is that both the use cases that you spelled out. have Clear impact as well as being good business opportunities. And clearly you're both mission driven and you've expressed a strong impact focus for the company, which I think is great. If you didn't have that, are there use cases for the technology beyond impact? And if those came about philosophically, how do you think about those? And and would you pursue them?
Bessie Schwarz: Yeah, that's a great question. It's the kind of thing that we and the team talk about a lot. And I'd say over the couple of years, especially 'cause we started really trying to solve a problem and decided to a VC backhoe scale tech company was the right avenue for it.
We believe there's actually no silver bullet to this Impact revenue trade off. I believe that it's really a matter of process and accountability on a really a day to day basis, 'Cause those are hard decisions. There's no clean decision. Like, well, if you only did, if Cloud to street only did this or only helped this kind of insurer put a hard line here, I don't think there's any version of that.
I think it's a, a day to day basis of looking at it that said we have had things that we have said. No to And we have had things that we thought we would say no to in the beginning that we took a hard look and I think that can [laughs] probably shared some of those examples. So there are plenty of use cases.
or other markets like finance or real estate or others that have certainly come to us with interest in using our data. For a variety of different purposes, we've done some of that work and we're excited about doing it in the future. One of Cloud to Street's real strategies is hyper focus. So we're very focused on floods and insurance and governments.
Right now, we probably will move on to these other markets and excited to partner with others in doing that. That said, we do think that there are, you know, it's Possible that we could use the insurance to help make a business model more sustainable. That increases climate change for instance. And that's definitely something that we are not interested in doing.
And so what I would say is there are versions of the use of the technology that. doesn't Comply with Cloud to Street's mission to make the world climate resilient and enable everybody to have access to the information they need to prepare and respond to climate disasters. There are versions of the markets that we're in today that could use our technology to do that.
And we're pretty clear-eyed about what making those decisions. And we'll continue to kinda hold ourselves accountable as we go for it, but there's no kinda hard line. as I was saying.
Jason Jacobs: Beth, anything to add. That was a no for anyone that can't see, Beth [crosstalk 00:44:58]-
Dr. Beth Tellman: Sorry [laughs]. I was, I was-
Jason Jacobs: [laughs].
Dr. Beth Tellman: ...trying to go like, what about things we said no to that. Bessie was trying to serve up for me to talk about, but [crosstalk 00:45:06]-
Jason Jacobs: I mean, I can think of an example right off the top of my head where, you know, it's kind of a gray area of like, let's say a hedge fund came to you and said, we want to short real estate in the region's most prone to floods, you know, can you help empower us to profit off of doom as an example?
Bessie Schwarz: Yeah. So that's the only use case that we've thought about. And frankly, I do think that there already is a climate bubble in this country right now. I think we incentivize in many places development in areas that we well know should not be developed in. It's interesting that I don't think a lack of data is actually the problem in that case.
And ironically, in some places. The poorest and the least supportive people live in flood prone areas is that's paper found. And in some places it's actually some of the most valuable land. And it's continued to incentivize building in that place. I'd say the answer is maybe we might not do that, but frankly, I think that that is happening and going to happen no matter what.
And so cloud. to Street Wants to be able to be in the conversation around that and help, you know, steer the capital markets in a way that can incentivize climate resilience rather than continuing to shore it. So my, you know, the answer is probably not, but you know, everything's more complicated than it seems like.
Jason Jacobs: So if cloud to street is successful beyond your wildest dreams, what have you achieved?
Bessie Schwarz: Yeah. I mean, we'd love to take the protection gap from 70% of losses, not insured to 0%. And the way that I think about climate change very ...you've asked me a very broad questions, well, I'll give you a very broad answer and that that's always getting, bringing it back down to the human story.
But yeah, I mean, if we look at climate change really broadly, and the challenge that humanity is facing. We have to stop the problem. There may be some real solutions to actually just reverse some of the problem. But the fact of the matter is we've already have a lot of the impacts, especially for frontline communities already baked into the atmosphere and already being felt today. So we have to figure out ways to absorb this risk in a way that is even more equitable. than Previous ways that we've identified risk. I believe there's no amount of public dollar right now. That's gonna be able to absorb that. And we have to look to insurance and capital markets in order to be able to do that and what that looks like.
Actually, it's just balancing risk around the world. So the risk massive amounts of risk in California can be balanced by the risk in Rwanda and the communities that were there. If we do insurance in strategic ways. So while it's flooding in California, probably it's not, or may not be in Rwanda or Germany to, you know, new England on Louisiana.
And so we really seek to take that protection gap down to, you know, probably will never go down to zero for a variety of different reasons, but down to single digits, By working with not just interest, but working with the government counterparts in order to, to do that, we also very much believe that every community deserves access, transparent access to flood risk information, historic and near real time as it's happening.
So the kind of thing that happened, to the communities Beth worked in El Salvador doesn't need to happen again. And we believe that goes not just through the government, but I ...a productive government's working with insurance, working with the economy and the financial business industry in those locations too.
So first stop is access to information for all governments in the developing world. And then we're moving into taking down the insurance protection gap and then looking to solutions more, more broadly so that all communities have the protection that they need.
Dr. Beth Tellman: Similar vision. and I would say there's three things I'd really like to see different about how flood risk is managed worldwide.
That I think we can make a real difference in the first again, kind of Bessie talked about going back to the El Salvador story. Nobody's left out of flood aid in response who nobody's left for any reason. And there's transparent data on who's affected aid is delivered faster and it's given to the people who need it most.
And I really think we can help enable. That change because it's not happening around the world right now. Second is that no one has a lack of access to financial capital who needs it to recover from floods. And so that's developing risk transfer policies from every scale from governments pooling their risk to insure each other.
This is called sovereign insurance to municipalities. and Cities being able to fix and insure what they need after global flood event, down to farmers who right now are often forced to sell off critical livelihood assets or pull their kids out of school to buy seeds for the next season. And that's affecting their sustainable development. But they could have insurance policies to smooth out that variance in disasters from floods. Then they wouldn't have to have those livelihood gains personally, or their countries wouldn't have to set back decades in development, which sometimes happens in flood events. And I think that we have the data that can enable new types of risk transfer solutions.
That means that whoever needs access to capital after a flood event, Can get it and they can continue to sustainably develop their livelihoods and their country. And I'd really like to see that change in the world. The third is managed relocation and retreat, where it needs to happen. There are a lot of communities that have experienced flooding time, and again, that are going to continue to experience that under a climate change world.
And I'm hoping that our data can be just part of the solution. that They need to lobby their politicians and Congress people, and whoever has the power to change and give access to capital to relocate their communities. There's a lot of communities that don't wanna continue living in floodplains that don't have the capital to move.
And so I'm hoping we can add, add some data and evidence that they can use to lobby and, and get the resources they need to live somewhere safer.
Jason Jacobs: And. if you could Change anything that's outside of the scope of your control that would most accelerate your progress to fulfill this vision? What would it be and how would you change it.
Bessie Schwarz: Yeah, that's a great question. I mean, I think two things come to mind. One is really spending more money, mostly at the government public level on preparation right now, something like 97% of all disaster capital spent After the fact not taking actions that can reduce risk or put in better response in place and prevention and preparation in the disaster space is just like it.
in everywhere else, that $1 spent to reduce risk ahead of time. Is you know, something between like worth five to $7 after the fact. And just with the amount of risk that we have today, we can't afford to do it the expensive way. I think one kinda strong thing that we can do here is change the national flood insurance program here in the US and expand the we're making big steps forward, I think during this current administration.
But I think the way that we, the types of insurance. That we need to be able to nibbling around floods in the US need to change. Like everyone here knows the maps are insufficient. Everyone here knows a lot of the stuff that in the industry, there are a lot of stuff that Beth and I were talking about, but the way the regulation is now, we're not able to do some of the more innovative types of insurance products that we know helps reduce and absorb risk in the us.
Dr. Beth Tellman: I would say these are, to me, the wickedest problems that stand in our way would be probably corruption and institutional racism. There's been a lot of research. Some that we've done on social vulnerability and other articles that have come out over the past year, basically showing that if two communities are impacted by a flood of the same magnitude, one community is gonna lose more, And their livelihoods and property than the one right next door. And that's the community that has a higher percentage of people under the poverty line, or that have native American, black or Hispanic populations, according to the US demographic data. So that is the reality in historic underinvestment in flood mitigation.
And our housing policies in the US there's actually a term for this it's called blue lining. If you've heard of red lining, that causes a really specific bias in flood vulnerability that needs to change that we can't change with satellite data necessarily alone. And the second is corruption having Politicians that are not giving aid to the communities that need it. Most I've actually experienced in El Salvador people stealing food aid, selling it, or bringing it out in electoral campaigns to get votes. So that's a pretty serious mitigation of benefits that, that need to be received by people that are not. So that's the second thing I'd really like to change that I feel like is very out of my control.
Bessie Schwarz: Yeah. And I just to add on, I couldn't agree more with what Beth is saying and just from work in the US, there's some incredible work done at the local community level that is based on mutual aid that's communities, helping communities that I think putting more resources and support to that kind of effort. that Beth and I really only with data and the kind of effort we're doing, solving one layer of the problem, but the more that we believe, the more you can use that and all of the mechanisms financially and regulatory that we're talking about here to empower communities to help themselves is. I mean, I think ultimately the kind of theory of change that we're trying to lean into
Jason Jacobs: and where do you need help? at cloud to street. Who do you wanna hear from. If anyone.
Bessie Schwarz: We would love to partner with a lot of different folks. I would say that if you, are, you know, someone who is a government or humanitarian organization working anywhere in the world that needs access to information, we'd love to partner to help you do that.
And insurers exactly like I've been talking here who are interested, the other group I would point out and, and Beth may have more to add to this list, like all the job openings that we have now, but the community groups. Particularly in the us, 'cause we are a US based company that are doing work to build resilience for their communities.
We would love to support. You, and we really hope that we've built up a support and mechanism through data that can just enable community resilience. And coming back to this type of community empowerment and agency building that I was talking about that a community organizer uses. There's a number of groups that we really respect in the US, and we would love to help you. if we can.
Jason Jacobs: Beth, anything to add?
Dr. Beth Tellman: Yeah. Join our team We're hiring a lot right now to build this awesome company. It's a super exciting time to be a part of cloud to street. We're hiring hydrologists and radar scientists and a lot on the business and development and marketing side. So come be a part of this really exciting time and technology and let's work on giving people the resources they need to adapt to this unfortunately warming climate.
Jason Jacobs: Well, awesome discussion. Awesome mission, awesome progress, and so excited about what you're doing and about your past and the future. So thank you both so much for coming on the show and best of luck to you and the whole Cloud to street team.
Bessie Schwarz: Thank you.
Dr. Beth Tellman: Thank you.
Bessie Schwarz: This has been fun.
Jason Jacobs: Hey everyone, Jason here.
Thanks again for joining me on my climate journey. If you'd like to learn more about the journey, you can visit us at myclimatejourney.co. Not, That is .co not com someday. We'll get the .com but right now .co. you can also find me on Twitter @JJacobs22 where I would encourage you to share your feedback on the episode or suggestions for future guests.
You'd like to hear. And before I let you go, if you enjoyed the show, please share an episode with a friend or consider leaving a review on iTunes. The warriors made say that, thank you.
