Satellites, Smart Contracts, & Climate Change

The ultimate goal for Arbol is to be... Arbol is building the ecosystem, right? So, dClimate is where you enter, and you have every analysis tool that you want for your climate risk. But then, you don't need to top at analyzing. Arbol can then mitigate that risk. And the ultimate goal for this ecosystem is to be the one stop shop for any company, any investment firm, anyone who has climate risk and is looking to mitigate it.

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Welcome to the Space Capital podcast. I'm your host, Chad Anderson, founder and managing partner at Space Capital, a seed stage venture capital firm investing in the space economy. We're actively investing out of our third fund with $!00 million under management. You can find us on social media @SpaceCapital.

In this podcast, we explore what's happening at the cutting edge of the entrepreneurial space age and speak to the founders and innovators at the forefront. This is the Space Capital podcast, and today, we're speaking with Sid Jha, founder and CEO of Arbol, the parametric insurance platform for farms and businesses exposed to weather risk. He's also a founding partner of dClimate, the world's first transparent, decentralized market place where climate data, forecasts and models are standardized, monetized and distributed. We're gonna talk about both of those today.

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Chad Anderson:

We invested in Arbol's seed round in 2019 and again in the series A in 2020 alongside a great group of investors, and we're excited about what this team is building. With a background in applied math, economics and statistics, and advanced degrees from Harvard, Sid has built out agriculture commodities trading desks. He was previously director of multi-commodities trading at Castleton and cross commodities quantitative strategist at Citadel. And he's uniquely qualified to help us understand the revolution underway in ag, weather and space tech.

Chad Anderson:

Sid, it's great to have you on. Thanks for joining us.

Sid Jha:

Thank you, Chad. It's, uh, great to be on here. Thank you for inviting me.

Chad Anderson:

So to start, I think, you know, your background really helps tell the story of why you are the perfect person to be leading this company. Can you tell us a little bit about your background and what made you want to get into commodities in the first place?

Sid Jha:

Sure. So I came out of school in, uh, '05. I was at Harvard, you know, applied math and stats, bachelors and masters. And a lot of my career, as a result, was in intersection of, uh, quantitative analysis and understanding how markets worked on a very fundamental level. The first five years of my career was actually in interest rates, which is a very good foundation for understanding how all financial markets work. Most financial markets at their core are a reflection of where interest rates are, and understanding that in detail helps you to think about anything from public stock markets, commodities, venture cap, uh, and many of the broader trends that are ongoing in an, in the economy at any given time.

My first love was always commodities, ships, pipelines, you know, a lot of the base materials that drive our day-to-day lives. And, you know, how does food make it to our tables or gas flowing into our cars? And, uh, so I left JP Morgan to join what was then a startup hedge fund. And I was really focused on that intersection of quantitative analysis and fundamental understanding, though of markets that I have never encountered before. So everything from oil and gas to corn and soy beans, to copper and lead, and cattle hogs, you name it. So pretty much if it was even reasonably liquid, I have probably analyzed it and traded it in the commodity space.

And what that gave me is a very interesting sort of overview of how these different markets work from a production, consumption, logistics standpoint, and how they interact with each other. And then I left to, uh, start my trading desk. Went more from analysis into trading. And then lastly, I was... Uh, when I was at Citadel, it was about incorporating more cutting edge, uh, things like AI machine learning into the fundamental understanding of these very varied problems in the market. So commercially sensitive projects around crop yield analysis or, uh, power plant usage of various fields, and, uh, so on and so forth.

The common threat here was that weather and climate risks are, of course, a big part of these industries, you know, these multi-trillion industries have tremendous swings based on seasonal and other types of weather and climate risks that come around from droughts and floods to heat waves and, and, uh, and then, you know, variations in wind speed, and so on and so forth. You have, you know, a lot of value here that is at risk on an annual basis because, for example, a heat wave can cause a power plant to have to buy power at the stock market, because air conditioning demand has spiked. That power will be much more expensive than what they budgeted for. Or a wind farm is going to have problems if wind speeds are suddenly lower than average for the next few weeks, because they are going to be producing less power, they're going to be producing less, uh... And we go into credits and so on and so forth.

And of course, you have on the farming side droughts and floods are a big problem, uh, when it comes to farming all types of crops. And even when you do get subsidized insurance, it doesn't really kick in 'til things get really bad. And there are many situations where farmers are still left, uh, with large losses, even though they might be covered under a subsidized insurance.

So, this was the setup for the market, and on the flip side, you know, the market for risk transfer of these things was broken in, and when we started out Arbol. So, you know, it wasn't easy to o- over, offload weather risk to a different entity. And that's a big function of markets is transferring risk. And yet, markets were basically failing at transferring the most important types of risks, which were going to be even more and more important as climate pattern shifted and, uh, companies got hit with new types of risks that they haven't even budgeted.

Sid Jha:

So Arbol is a platform to help transfer those risks. And that came about basically from a lot of experience as both in the commodity space and blockchain and many others that, over the years, I've accumulated. And, you know, we actually started as a white paper on the blockchain space to say, "Okay, what if we could embed this insurance logic into what we now know as NFTs?" And the idea was that we would put in the insurance logic in the smart contract to read data like temperature data, and make payouts in a distributed system. Certain things were not possible from a regulatory standpoint, but we continue to strive towards that eventual goal. But this whole notion of an loss adjuster, like a human being coming to assess damage in a subjective manner leaves a lot of people hanging and leaves a lot of, uh, dissatisfaction with the insurance landscape.

And all of this became much worse with COVID, where you have tens of thousands of lawsuits going around whether a pandemic is covered and how do you assess damage, and such a scenario. And, you know, things are delayed quite a bit. You have clients going bankrupt waiting for an insurance check.

So, you know, putting this all together, the idea behind Arbol was that let's broaden the adoption of parametric insurance, insurance that pays based on data. And the biggest, uh, sort of use case is climate insurance, that climate risks are getting worse and worse, and that's what we need to address.

So, you know, Arbol started in 2018 and, uh, you know, Space Capital was, as mentioned, a very early supporter. And part of what the, the vision was that the improvement in data quality, like satellites that measure the weather or other types of things like crop meditation and a more and more granular level really helped to reduce one of the big previous problems of parametric insurance, which was basis risk. Like, what if the data says something, but then that something did not happen to me?

Chad Anderson:

Mm-hmm (affirmative).

Sid Jha:

For example, if you measure weather on 100 by 100, 100 kilometer by 100 kilometer grid, well inside, the weather can actually be very different for different people. So someone purchases insurance based on that data set, they might be left with, you know, a rain storm that did not get measured in the giant grid.

Chad Anderson:

Mm-hmm (affirmative).

Sid Jha:

But now if you make that, you know, measurement grid really, really small, like one kilometer, now the chance of, you know, this basis risk is much lower.

Chad Anderson:

And you're doing that with satellite data.

Sid Jha:

Yes. So a lot of the weather data is measured by satellite. You do have station networks globally, and often, data sets are blend b- uh, between station data, on which is on the ground, and satellite data. Now in different places, though, you know, that balance will shift, because once you start to leave really dense urban areas, even in rural US, and then, you know, emerging markets, forget about it. Like, you have a humongous gap in ground station data.

So there, you have more and more importance of satellite data to fill in the gaps basically. Like, we, we were in programs in places like Cambodia where, you know, the entire country might have one, you know, weather station at the airport in the capital city. And you basically cannot do anything without satellite data.

Chad Anderson:

When did you learn the power and potential of using satellite data for this? When's, were you using this in any of your previous roles?

Sid Jha:

Yeah. So in, in commodities, you know, one of the, the role I mentioned at, for example, Citadel, but even before that, you increasingly had satellites starting to come up through various different applications and companies that were doing pretty innovative stuff. So one very common use was the use of, you know, vegetation indices. So essentially, infrared satellites that measure how much greenery is, you know, coming off a particular area versus other colors to assess, you know, crop health. And, you know, in areas, a lot of places, like I used to trade a lot of wheat and, uh, corn...Aren't in other crops, you know, I- I- I- in a lot of the world where government official data is severely lagged and often not the most reliable, you really need to measure, what is the state of the crop in these different parts of the world, say wheat and Argentina, corn in Ukraine and satellites give you a really nice objective way to say, okay, this place is in trouble or this place seems to have a really good crop coming along.

And so, I was familiar from that standpoint. I was also back then an advisor to a group that was trying to launch one of the first, uh, commercial radar satellites. And, you know, I learned a lot about the satellite space from these different experiences.

So, when we started building out Arbol's data infrastructure, you know, we pretty much knew that, you know, satellite-based weather data, which would be the first leg was going to be key. And then also of course, vegetation data, like we are working on various products to run, you know, insurance programs, using crop yields that are estimated using satellite vegetation data.

And again, the thing is like in us, you have a lot of official government data that can be used as your data source for the contract, that doesn't exist in a lot of countries. So, ss-,you know when you're especially in emerging markets, you need to basically use satellite data to get at the heart of what the loss is likely to be on the ground. And sending people on the ground is really impractical there.

Chad Anderson:

Makes sense. And so, in terms of the inception of the company, I mean, it's clear that you've brought the entirety of your commodities background and your experience in, uh, these other technologies to bear. You know, when did you first see the opportunity for Arbol? What made you wanna leave your job and go off and start something?

Sid Jha:

I could see that, you know, having worked with a lot of these different commodities, that to me, it just did not make sense why it was so difficult to hedge weather risk or, or insure all these weather events.

For example, if you look at the Renewable Space, they carry a tremendous amount of wind speed and cloud cover and other types of risks, which to me, it makes a lot of sense that this would be a market there's an actual need. This is not just, a-, it is, that we have no speculators in our platform, right? We have all these people have a need to reduce risk, whether it is to get a bank loan, whether, or, or just to sleep easier at night, right? So there is a need here, but, and this is the other part of my experience and, you know, a couple of the other co-founders that, it's really important to then channel the right capital base as well.

And that was what was lacking here is; technology product is one side, and the other side is capital. And by capital, I mean, who is going to be underwriting this risk. And we were always stuck in this chicken and egg problem with these markets, right? Like you, when the market is very small, very few people want to put in capital to transact in it. It's risky, it's illiquid, it's concentrated. You know, the weather risk market was basically a few pockets of risk in certain parts of the US and Europe. That's not great diversification. Now you're taking up a lot of risk, you would charge a very high price for this. Well, if you charge a very high price, you're not going to get, repeat client business.

So, to break that feedback loop, we, you know, did a lot of the, some more tedious work of just talking on and on with different types of clients and really sort of understanding what is needed, which nobody had bothered to do, especially in the farming space. But when you started to have these conversations, you know, things started to click like, okay, a lot of these people need very similar things, and nobody is providing a product for them.

Chad Anderson:

Hmm.

Sid Jha:

Things started to, you know, um, kind of click in that there were needs that were being unmet and there was enough size that you could accumulate that then would get the capital side interested.

Chad Anderson:

Yep. The right place at the right time.

Sid Jha:

Yep. Yep.

Chad Anderson:

... With the right team.

Sid Jha:

Yeah. An old boss of mine used to say that most businesses are too early or too late, which is something very difficult to beat. So, just...

Chad Anderson:

Timing is everything in life.

Sid Jha:

Yep. Yep. Exactly.

Chad Anderson:

So Sid, w- I think so far we've mentioned blockchain, big data, machine learning, space tech and climate change. I think that's a buzzword bingo...

Sid Jha:

(Laughs).

Chad Anderson:

But in terms of your product, actually, each of these has a very practical purpose and I'd like to hit on those really quickly if we can, because, you know, weather and climate, common across all commodities. And Arbol is enabling farmers and businesses to hedge against climate risk and De-climate is tackling climate change, head on.

Sid Jha:

Yeah, sure. So, yeah, I'll go through the different things you mentioned. So De-climate came out of Arbol’s, more work on building a decentralized data network. We, as I mentioned, we started from the blockchain world and we built our Cloud on a, you know, essentially a decentralized Cloud. So, you know, IPFS.

By March of last year, we had, you know, built enough data pipelines, a lot of institutional great data that we could see other companies in the market charge, uh, rather exorbitant sums for, but things that, you know, we do not feel should be that expensive and it should be a lot more accessible. This is something that's actually starting to come up in more discussions about how the big companies are buying up a ton of these climate data outfits. And, you know, really making things is inaccessible for a lot of the smaller and mid-sized client base that is increasingly buffeted by climate risk from municipals to small businesses.

So, we basically took dClimate, poured it over into its own separate decentralized network. And it allows a community to contribute and use climate data, information models and, and, and a host of other sort of things that are allowing us to understand our climate better. By creating this community. You know, we also get to leverage the best in class of what's going on in the climate space rather than having some internal siloed system, which can never realize the full potential. One example is in carbon, right.

So we are, dClimate has been making a lot of progress in carbon verification. And this is something that of course is not Arbol's day to day work, but Arbol gets to leverage that work over time and dClimate is branching off into many different directions as the market needs growth.

When you mention big data, I mean, that's just sort of the heart of all of this. Some of these data sets are truly massive. You know, we have like hourly or sub-hourly data sets going back 40, 50 years. And it's not just about any one data set. All these data sets, interact with other data sets. They're all ins-, you know, pipelines that update automatically. We have forecasts that cover the globe adding more over time, we'll be adding stuff on crop yields, uh, as I mentioned, carbon, biomass data. So any aspect of climate, De-climate is going to be touching. And in ss-, relatively stealth mode, our API has already, you know, over a million requests a month and over 1300 unique users, many of which are some of the world's largest commodity companies, which shows the latent need in the market.

And we haven't even come out with the flagship platform yet, which is coming out soon, but the needs are there. And our API is open for everybody to use. We would love to have more people using it and really see how clean and easy it is to get weather and climate data now compared to what's out there.

So, that's on that side. And then Arbol is an anchor client of dClimate and all of the dClimate data that's there. A lot of it is used by Arbol to set up these structures, these insurance contracts. And it can be as simple as, uh, farmer getting paid, you know, rainfall is below average or the month of July in his, R area, or it can be very complex, you know, blended sort of data set between wind speed, solar radiance temperature, which kind of reflects the demand and supply of a renewables company.

Temperature is a big driver of power demand, so uh, from that, and a whole range of contracts in the middle. So these are all structured by Arbol, the pricing is an AI engine. You know, one of the things we realized was that the big problem that where the insurance industry has is that it lacks scale on many different aspects, not just one, right?  So the loss adjustment is done by data on our side and the insurance industry is done by people going out through the site. So that's a problem of scale. The pricing is done by a staff of underwriters who sort of use a mix of models, but also human subjective analysis.

And to me, this is how Wall Street was run and increasingly is not run that way. And I-, I'm w-, trying to bring the systematic trading background that I had into this field. And in terms of data sets, you know, we have an extremely flexible platform. So De-climate can ingest all types of different data. And we mentioned things like satellite, uh, you know, a lot of our data sets of course use satellite data. Um, you know, for us, that's a big area of focus. We are adding a bunch of stuff there around emissions, around carbon sequestration, crops, soil moisture. Uh, a lot of this stuff is assessed by satellites and for us as we grow the array of data sets that we can add will be a key advantage for us in developing products, then that the client wants

Chad Anderson:

Makes sense. Well, look, I mean, Parametric insurance has, holds a ton of promise. I mean, from all the inefficiencies of insurance that translates into extra cost that prevents a whole lot of, of farms and businesses and anyone from getting access to the insurance that they would like to purchase.

I'd like to talk a little bit about your progress and the traction that you've made. So you've gone from having, you know, an MVP of your product and your platform a little over two years ago to some pretty incredible growth today. And I think a lot of that has the do with the, that there's just so much demand for your product, the, the long tail of demand here, right?

I mean, insurance is really catering to the large businesses who have had, you know, really no difficulty getting insurance products, but this long tail of demand is, is big! You know? I mean, how big is it? How big do you think Arbol can get, you know.  Tell us a little bit about the trajectory that you're on.

Sid Jha:

Yeah, it's been exciting to see us really filling various coverage gaps that, uh, I think the insurance industry was either... There was not much of an acknowledgement that those were very large, I think, or how do you fill those gaps. Right?

So, yeah, in 2020, our gross premium was around 2 million, and 2021 was 70. So, you know, that 35 rex growth, and, and we already have a whole pipeline for this year building up, but I think, uh, you know, the range this year, we are targeting anywhere from 200 to 600, really depending on some of the stuff that we're setting up on the capital side.

So, you know, the growth rates that we have seen have come also... What's been great has been the diversity of client base. It's come from agro businesses, it's come from renewable energy, uh, producers, it's come from traditional energy guys, natural guys, lot of different aspects of our commodities landscape.

We also are starting to move into areas that are not just commodities. We have a pretty interesting that, uh, we are aiming to launch this year in partnership with a platform that, you know, for things like vacation rental home bookings. You know, you rent a house in the Hamptons every, uh, summer and let's say it rains every single day, maybe you can get a refund for something like that.

So, there's a lot of other applications as well that we are starting to see, and a lot of them are actually inbound requests, that, "Hey, is there a way to, uh, have a product for this because it's really impractical to do things in the old school way?" There's a lot of scope here, and, you know, for us, I think the trajectory that we are on... I mean, to me, getting to over a billion in premium is really not that much of a stretch over the next couple years.

So, you know, it's, it's 2 million, but we started in 2020 from an MVP and to see this kind of demand has been great, but I think we are just scratching the surface. Our growth from 2 to 70 million has been with, uh, you know, a couple of sales people and just two major regions of focus, the US Midwest and, uh, parts of Europe. We have a lot more to go. We're having issues going on in Latin America, in other parts of North America, in parts of Europe, and as I mentioned, there's a lot of non-commodity industries that need to start also, uh, hitting where we haven't even scratched the surface.

Chad Anderson:

So, if I'm hearing you correctly, that your beachhead market, ag, you know, that there's $1 trillion of crops that go uninsured every year, and even just corn alone in 2019 was more than 3 billion, right? So, 1 trillion in crops uninsured every year, that's the beachhead market, but then there's many more opportunities. And I've heard you say before that 70% of all businesses, of, of world GDP are impacted by weather. So, the opportunity here is much, much bigger than a trillion.

Sid Jha:

Yeah, the TAM is, uh, total addressable market is, is tremendously large, it's all about executing. So, and, and the thing is that once you start to gain traction, the speed can be extremely large because you have found a product that you'll find that tons of clients have this need. So, you mentioned ag as our beachhead market, and it indeed was, and still is a very important market for us, but energy's actually, uh, quite a bit larger now, and this all happened between, you know, in the second half of 2021.

So, once you land on the right product, you know, you find that there's so much latent demand because people are struggling with climate risk. When we started Arbol, we actually did a study to scrape every single FCC filing, and these are large... These are public companies, so they are obviously larger than your average company. But even in that, there were thousands of mentions of losses due to weather risk across every sector, from retail, to oil, to agriculture, and many others. You know, and a lot of this stuff is just, for now, just carried as, you know, uh, an act of God or whatever, that people use to just say, "Okay. We can't do anything about this."

The ultimate goal for Arbol is to be... and it's... Arbol is building the ecosystem, right, so dClimate is where you enter and you have every analysis tool that you want for your climate risk. But then, it'll need to stop at analyzing, Arbol can then mitigate that risk. And the ultimate goal for this ecosystem is to be the one stop shop for any company, any investment firm, anyone who has climate risk and is looking to mitigate it. And that list is growing by the day. You know, every single bank, for example, is being pressured in different jurisdictions to measure their climate risk. You have a loan portfolio of mortgages, I can guarantee you there's flood risk, there's hurricane risk, there's wildfire risk, all sorts of risks sitting in there. And until recently, nobody bothered to quantify those. Now they are starting to quantify it.

But to me, that's only step one. You are quantifying it to satisfy some regulatory need. You will soon need to mitigate it to satisfy your investors, your stockholders, your board members and Arbol will be there to address that need.

Chad Anderson:

Exactly. We're seeing all these tailwinds, um, and we're seeing actually some... We're starting to, to lean in that direction, and we're starting to see companies use this as an opportunity to lead, and actually use it as a competitive advantage. And so, you've got the world's largest financial institutions using their influence to drive change, you've got the world's largest asset manager, BlackRock, stating its ambition to achieve net zero emissions across their entire AUM in the next couple of decades. TPG in Brookfield also going in, Microsoft is doing a lot here. And, uh, you know, I can go on and on. But with all of these tailwinds then, what's the issue? What is it that dClimate is solving for?

Sid Jha:

So, dClimate and Arbol will solve different issues. So, dClimate's issue is that... The issue dClimate is most focused on is that the entire climate information landscape is siloed, expensive. I mean, you... It, you know... If you want to run hurricane simulation analysis, uh, it can cost $10 million dollars plus for subscription. Right? So, who can afford it? Just the world's largest insurers. And what happens to, you know, a municipality that's in the path of hurricanes frequently, or, you know, a small, uh, industrial business which has factories in a hurricane zone? It's inaccessible, it's siloed, and it's very difficult to navigate. There is a lot of free data out there. It's... You need a team of data scientists to parse through and understand what they mean, how they fit in, and they're not built for user friendliness. What's free is not user friendly, what is user friendly is not free, and it's not free at all. It's very expensive.

So, that's what we're trying to... As a step one, take care of that. The second level with dClimate is let's not just make a data platform, let's build a community that can come together and start building analytics, and forecasts, and other useful tools for the community. So we have people building visualization tools. We built a tool for the construction industry where they can check how many days of work they might lose, at a um, site. This is something that was requested to us by large, you know, insurance brokers that deal with construction companies. There is no such tool out there for site managers to easily assess their risks.

And so, small example of how, you know, industries carry climate risk, but they have no real way to analyze them. Just having raw data in of itself is not going to do that. Now, another market that we have talked about before is carbon. Carbon's another great example. So, carbon offset markets are extremely opaque. The measurement methodologies are super old school, often having to send people on the ground and really kind of getting there with ladders and tape measurers, which is fine for a forest in North America. It's not going to work for most forests in tropical countries where you absolutely need to save them.

So, that's one aspect, is non-scalable methods which, as you might remember, was the same problem of insurance. So, one of the things we're working on is a new kind of offset that would be accountable on an ongoing basis. How do you make things accountable on an ongoing basis? Well, you have satellites that measure whether you cut forests or not and have payments contingent on that. This is something that is where the climate space needs to move to, the carbon space does but because we are not utilizing the cutting-edge technologies that are out there, we have been unable to do so, and that's what dClimate is pushing for on the carbon side.

Chad Anderson:

Hm.

Sid Jha:

So, that's the dClimate umbrella, really. It's about shining a light on all these opaque, siloed problems in the climate information space.

Chad Anderson:

Sid, we're saying the same thing. I mean, it's really... From our perspective, it's all about measurements and markets, and we've heard customers of these carbon offsets say the same thing, is that it's difficult to go out and spend real money on carbon offsets when there's so much discrepancy of, you know, between what is self-reported, what is being measured by objective third parties. And so, you have put a lot of emphasis on this, in terms of the auditing, and the transparency, and to help build trust in our systems, and the block chain, and the decentralized network plays a key role in that, doesn't it?

Sid Jha:

Yeah, absolutely. So, the combination of algorithms and data with block chain is what allows for essentially, public auditing of your models, right? So, dClimate is not trying to build some black box secret model, they couldn't patent it. The models for verification of carbon sequestration, carbon emission, all this stuff will be out in the open and anyone can audit it. If you have a model that's better, well, let's horse race it. You will be able to see all

All the metrics. And if you have a model that's better, we are more than happy to incorporate it into the ongoing verification. And I think that's where you need to get to. This is not a space that is going to move forward if you just have siloed models. And you know, this is, uh, going to sit in my vault it's IP... Uh, you know, it's patented and I can't tell you too much about it. You're not going to make a lot of progress then. So we are very, very keen on having it be as open-source as possible.

Chad Anderson:

And so where are you at in terms of- of the platform? Is it up and running? Are you selling offsets for carbon now? Can, you know, can people come on the platform and- and buy? 'Cause I know that a lot of these big companies are- are-

Sid Jha:

Right.

Chad Anderson:

... Looking to do that.

Sid Jha:

dClimate overall has a flagship platform for all the data stuff. That's in testnet, and it's coming out soon as a full launch. That'll be sometime this month as a testnet. The asset stuff is being worked on. We're putting a lot, uh, a lot of work on the modeling and making sure that we come out with something that everybody can trust. And so that we are expecting, you know, probably sometime in April. But the flagship platform for dClimate itself for contributing and using the data will be usable anyway, that the offset project is sort of one of many projects that dClimate is basically working on pushing forward, all part of bringing transparency to climate. dClimate's API is usable already. And, uh, as I mentioned, we have a lot of users for all the different, uh, weather and climate needs and that's just api.dclimate.net.

Chad Anderson:

Got it. So 2022 is gonna be a big year?

Sid Jha:

Yes.

Chad Anderson:

So there is clearly money to be made here. I'm just curious, you know, we're seeing other companies pop up raising some venture rounds. Who's actually doing things in this space? Are there other competitors that are on your radar?

Sid Jha:

So on the Arbol side, you know, there are some parametric insurance companies. The difference is that we actually don't end up competing too much with the other insurtechs. And part of the reason is that the types of transactions that we have and the type of distribution we have built, it's not easily accessible by the standard broker markets and things like that. And the market is growing so fast that we haven't needed to overlap yet too much. The type of capital we have, we don't, uh... You know, we- we prefer different kinds of transactions than the insurtechs, which rely on traditional reinsurance capital. Remember our capital is... it's Wall Street Capital. Is non-insurance capital. And so we prefer different types of transactions than they do. Like we are not into writing super- super tail auctions. But the industry tends to prefer that.

So, there are some companies out there, like DCart, uh, is in the parametric space, but again, we have, uh, limited overlap with what they do. On dClimate... dClimate is a very unique business model. I mean, there are climate risk analysis platforms out there like Jupiter and others. dClimate is a much more decentralized entity, and so it is evolving very rapidly, but also in ways that are, I think not really overlapping with a lot of these guys. At some point that may change.

Chad Anderson:

Okay.

Sid Jha:

But that's where the power of the ecosystem also comes in, right? dClimate may help you measure your climate risk just like many other platforms, but then it has Arbol as part of that ecosystem to help you mitigate that risk. That's something that is lacking elsewhere. So I'm sure there'll be more competitors coming, but we have so far, you know, not really encountered much in that way. Partly because it's an immature small market. It's a tiny percent of the insurance industry, but it's growing very, very fast. So, you know, when the pie is growing and you know, it's a small market to start with, everyone's building this, you know, sort of in their own directions.

Chad Anderson:

So it really is all about execution as we know, and as you mentioned earlier. Um, you've built a really impressive team. I mean, in- in addition to yourself, the founding team is exceptionally strong. A lot of experience in this category. But you're a young company and you've actually gotten your chief insurance officer, for example. Um, you were able to poach them from a large insurer, right? So can you talk a little bit about the team and why you're gonna continue out executing?

Sid Jha:

Yeah, one of the things that from day one I was very focused on was that this was going to be a very complex endeavor. It touches on everything from data and technology on one side to regulatory legal and, you know, sort of capital flows from non-insurance industries. So it requires a large number of points of expertise that essentially is not possible for one person to have. So the president of Arbol like CFO/COO Phil, uh, is... for example, he started markets in the late 1980s doing currencies and then, uh, was running Global Emerging Markets at AIG in the 90s. And then on his own for 20 years doing a lot of Emerging Market Private Equity stuff. So a lot of in depth, you know, even a member of the AA in New York border trade. So a lot of in depth experience on how sort of the... you could call the- the old school plumbing of these different markets work.

And then on... You mentioned, uh, our chief insurance officer Hong, he was an early supporter and joined us in March of last year from after a 23-year career at Black Carpenter. Again, a tremendous amount of in depth knowledge about, uh, the insurance reinsurance space. And, you know, on the other side, you know, we have our CTO and chief data scientists and they have, uh, a lot of experience working with a large amount of different technology teams and data.

And so part of my job is to make sure that the two worlds bridge well, right? Like my premier job is to make sure that the firm runs in a way that is... you know, it's integrated well between the sort of new school industries and the old school industries that need to come together for something like Arbol. This is not a pure tech company. It's very infused with technology, but in the space we operate in, it nee- needs to fit into the regulatory legal, you know, the insurance world, the derivatives world, the securities, rules that we have to follow and all of that needs to work in unison. And so this has all happened because we have so many different points of expertise, all working together as one team.

Chad Anderson:

Well, like as an early investor and somebody who's been following your progress since the beginning, I have to say, I mean, this is really an exceptional team that has done an amazing amount in a short period of time. So credit to you and the team. Sid, before we go, just wanted to ask, you know, how can listeners learn more about, uh, Arbol and dClimate and get involved in what you're doing?

Sid Jha:

Yeah. We'd love to have, uh, more people reach out. Arbol, um, you know, our website is arbolmarket.com and, uh, we're active on, uh, LinkedIn and Twitter. And, uh, dClimate is www.dclimate.net, also active on, uh, LinkedIn and Twitter. So, please reach out. We'd love to have a discussion. There's just so many different industries and different fields that we touch that there is often, uh, really interesting overlaps that we find when we have conversations with all types of different clients.

Chad Anderson:

Great. Sid, it's been great talking to you today. Thanks very much for coming on the show.

Sid Jha:

Thank you Chad, for having me here. And it's a great discussion. Talk to you soon.

Chad Anderson:

Thanks for tuning into the Space Capital Podcast. If you enjoyed this episode, please leave us a review and subscribe to make sure you never miss an episode. And if you're interested in learning more about investing in the space economy, I invite you to visit our website, spacecapital.com, where you can get access to more industry-leading insights and learn how you can join the entrepreneurial space age.

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