Jacob Goldstein
Jacob Goldstein spent more than a decade as co-host of the Planet Money podcast. He's also the author of the book Money: The True Story of a Made-Up Thing, which the New…
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Sid Jha is the CEO of an insurance company called Arbol. Sid’s problem is this: Can you make insurance cheaper and more accessible by using new technology, new sources of capital, and new ways of thinking about risk?
In this episode, Sid explains:
- How climate change is affecting the risks Arbol covers
- How Arbol is competing with giant insurance companies
- Why prediction market contracts are good for betting, but not hedging
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Pushkin. I'm Jacob Goldstein, and this is What's Your Problem? My guest today is Sid Jha. Sid is the CEO of Arbol, an insurance company that he founded in 2018. Sid's problem is this. Can you use new technology, new sources of capital, and new ways of thinking about risk to make insurance cheaper and more accessible? And let me just say right up front here that I love insurance, and I'm not afraid to admit it. Insurance is a way of thinking about the world, a way of thinking about risk. Insurance tells us that in the aggregate, a lot of the most important risks that we face are in fact not random. They are predictable. They are quantifiable. And over the last few centuries, People have built on this insight and they have turned insurance into what is really a financial technology that's essential to the modern world. That is why I love talking about insurance. In our conversation, Sid and I talked about the kinds of risks that his company covers, everything from bad cotton harvests to hurricanes. We talked about climate change and we talked about how Arbol, how Sid's startup, is competing with giant companies that have been selling insurance for generations. To start, We talked about the big picture.
01:33
Speaker 2
Insurance is one of the key pieces of infrastructure for a society to grow and honestly function.
01:40
Speaker 3
Almost every decision you make.
01:42
Speaker 2
About how your finances are deployed or how much you save versus invest, underlying it, you are assuming that you are insured on a lot of things. So imagine a world where you don't have health insurance and you don't have home insurance. Think of how much money you would have to keep aside for self-insurance.
02:03
Speaker 1
Well, you couldn't get a mortgage without home insurance, for one thing. So first of all, you'd have to save up to pay cash for your house, right?
02:10
Speaker 3
Absolutely. Absolutely.
02:12
Speaker 2
But, you know, that's just one because you're kind of required for it. And that's because the bank is required for it. So if you think about the banking system and lending and insurance are essentially sister activities. A lot of lending cannot happen without insurance because then if you don't have the right insurance, then the interest rate a lender has to charge to satisfy that risk can be exorbitantly high. And I lived in India until I was 11 and I'm very aware of the economic setup there. If you look at countries with low insurance penetration, one of the things that becomes very obvious is how high the cost of borrowing is or how much capital is trapped to essentially cover unexpected outcomes. And this goes from families up to big infrastructure projects.
03:01
Speaker 1
And like specifically, I mean, you mentioned... being a little kid in India, as you mentioned that, are you thinking of something in particular? What kinds of things did you see that are representative of what you're talking about?
03:13
Speaker 2
I mean, there's a plethora of these things. Back then, I was there in the 90s, and it was a very challenging time in that country. I mean, a lot of families had to keep money aside just to cover costs of the death of a loved one or unexpected medical emergencies. Home insurance was a non-existent concept. My grandparents' family lost their house in flooding. There's no insurance to rebuild that. It is just restart saving again to rebuild this thing. Crops used to get lost all the time. There was no crop insurance. And so your whole life revolves around the cycle of debt that you have to go into every time there is an unexpected event. So you're a farmer, you got a rice paddy or a sugarcane field, that goes out. That year, you're going to go to lenders to borrow money to survive. That interest rate can be in the hundreds of percent.
04:06
Speaker 3
At best, you might get 50 to 80%.
04:08
Speaker 2
That is a cycle of debt you're very unlikely to get out of because next year, even if the crop is good, you're just barely surviving.
04:16
Speaker 1
So we have more than that, but at the time you're starting... Arbol, what are the meaningful, practical problems with insurance? What do you see as the limits of insurance that you think you can improve on?
04:32
Speaker 2
When we were starting Arbol, climate was just starting to become bigger discussion. So when you have areas with higher volatility of outcomes, and that could be hurricane or hail or severe convective storms or wildfire, you have a lot more of the population living in higher volatility areas, whether it's coastlines or the Midwest with the hail zones.
04:55
Speaker 3
And you've seen losses really ramp up over the last few years.
05:00
Speaker 2
So what insurance was designed for was a different pattern of population and risk. So when you brought up climate change, a lot of this is not necessarily just climate change. It's just that populations are living closer to the forests or coastlines or in hail zones and many other sort of.
05:15
Speaker 3
Vulnerable areas, right?
05:17
Speaker 2
So As these shifts are happening, the insurance system I see as still very inflexible. You have lots of intermediaries. So from customer all the way to the reinsurance capital, you have probably at least five, if not eight to 10 layers of intermediaries. So one is that the insurance you pay for, a large portion of that can be just the fees to get the risk from a customer origination point all the way to capital.
05:46
Speaker 1
So it's like too much intermediation is making it more expensive.
05:49
Speaker 3
30, 40% of your premium can be fees.
05:53
Speaker 2
Wow. But it's not like everybody's, you know, making money hand over fist.
05:58
Speaker 1
There's so many different players between me, the buyer of insurance, and the ultimate... person who's actually supplying the capital. And it's not like any one person is ripping me off. It's just an inefficient system.
06:10
Speaker 2
Yeah. You will often have like five, six companies involved in an insurance deal. And each of them has to obviously make money for their shareholders. And it just becomes this very difficult system to streamline. Then on top of that, you have a humongous patchwork of regulations, right? So different state regulators and everybody has different modalities on how you incorporate even new types of models. And then finally, this system, the way it is, then makes it very difficult for different capital, new capital pools to enter the market. But that compounds the problem because new capital wouldn't make it more affordable. So you have a bunch of compounding issues all circling around this difficult to model, difficult to write sort of areas which are, you know, the climate risk has increased a lot and the property values in a lot of these climate sensitive zones have increased a lot. And so that combination is what's making insurance affordability and insurance availability more and more challenging.
07:10
Speaker 3
That's the baseline, right? But life is not static.
07:13
Speaker 2
You have new kinds of risks that are popping up like AI data centers that are so enormous in scale and have such complex risk structures. And you're seeing the insurance industry struggle to meet that demand.
07:30
Speaker 3
Oh, interesting.
07:30
Speaker 1
Like I'm building a whatever billion dollar AI data center and I want to insure it. And the insurers are like, what does that even mean? And how do we do that?
07:40
Speaker 3
Exactly.
07:41
Speaker 2
There's so many types of risks. There's climate risk. There's mechanical failure risk. There's actually a ton of revenue risk because if, let's say, you have a transformer or something that gets damaged when a hurricane hits a data center, well, The loss is not just the loss of that transformer, it's the fact that you might be sitting in queue for the next two years to get a new one.
08:01
Speaker 3
And what does that do to your revenue profile?
08:03
Speaker 1
There's also political risk, right, at this point.
08:06
Speaker 3
There's a lot of that.
08:06
Speaker 1
They will suddenly say, you actually can't build the data center that we told you you could build.
08:10
Speaker 3
Exactly.
08:11
Speaker 2
You know, we're going to be putting out some stuff on this where we are doing a bunch of work on analyzing climate risk. And as new data centers are popping up in areas that are, you know, a little closer to the coast or in hail zones and many other higher risk areas. And, you know, we do a lot of climate modeling in-house.
08:28
Speaker 3
And so we think we have.
08:29
Speaker 2
A good view on how the risk characteristics of these data centers is changing as new ones are getting built. To me, one big issue is that Most of the data center boom has happened in the last couple of years where you've not had major hurricanes hit many areas. And so I think it's still a new concept for a lot of these guys. So you have property on the coast, you have crops growing in an area where insurance coverage is muted.
08:58
Speaker 3
You have wildfire prone areas. All of that is stuff we cover.
09:05
Speaker 2
We go in areas where the incumbents are scared to go into, whether because the risk is difficult to model or their capital structure is not built for it. We bring technology, we bring novel capital. It's a marriage of technology and capital to solve the end problem, which is I can't get good coverage. If I get coverage, it's too expensive or it's got too many exclusions. And that's what we're trying to solve.
09:31
Speaker 1
So when you started your company in 2018, you focused on this kind of weird type of insurance that hasn't been used very much historically. It's called parametric insurance. And let me just say what the basic idea is, and we can talk about it. Like, say I'm a business. Traditionally, I can buy insurance that covers me if something happens to my business, if I get robbed or if my factory burns down or whatever. But parametric insurance... is different, right? It's this type of insurance that pays out based not on what happens to my business, but based on some objective thing that happens out in the world. So, for example, I might buy a parametric insurance That pays off if there's a certain amount of rainfall in a certain place in a certain period of time, or if the output of some particular crop in some region is below some threshold, this kind of thing. And so I'm curious, like, who is the customer for that? You know, who out in the world is not being served by traditional insurance and needs parametric insurance?
10:38
Speaker 2
So when you start out, right, in a very difficult to traverse market like insurance with a ton of large incumbents, you have to find the right wedges to build on.
10:49
Speaker 1
I mean, you need somebody who's really not being served by what's currently available.
10:54
Speaker 3
Exactly.
10:54
Speaker 2
Our biggest one was actually cotton gins. What was one of our early sort of home runs, if you will. So a cotton gin sources cotton from a bunch of counties sitting in, let's say, Texas. And if that cotton crop fails in those counties or is well below average, Those gins have trouble. And we actually have a great blog post from a few years ago about a gin that actually came to us and said, we really helped save their business from our payout because the cotton crop was terrible back then.
11:22
Speaker 1
You say cotton gin, I think of Eli Whitney, but today a cotton gin is like a company that is spinning cotton into thread or fabric or weaving?
11:32
Speaker 2
Yeah, taking the raw cotton and coming up with the middle product, if you will. Then other companies will take that and So a lot of the cotton gins are small to medium-sized businesses.
11:44
Speaker 1
And what are they actually making? What are they turning the raw cotton into?
11:48
Speaker 3
It'll be something like yarn, basically.
11:50
Speaker 1
Something like yarn, okay.
11:51
Speaker 3
That can then be used by a larger company.
11:54
Speaker 2
And they'll be involved in a lot of different related operations, like warehousing, transportation of cotton, and things like that, all of which depend on a cotton crop. Right.
12:03
Speaker 1
And unlike the farmer, that small or mid-sized business can't buy like federal crop insurance, even though they are very largely dependent on the local crop.
12:14
Speaker 3
Exactly.
12:15
Speaker 2
So now if we dig deeper into this wedge, and it's more to show our thought process, and this was where very, very challenging in the beginning. You go after the wrong market early and it's lights out, right? So here you have a high correlation to revenue with that risk.
12:33
Speaker 3
You have official US.
12:35
Speaker 2
Government data on county level yields that market trusts, and you have capital providers who like that lack of correlation, because this is not even correlated to cotton futures. Cotton futures trade off of a global balance sheet. This is like local West Texas cotton output.
12:54
Speaker 3
This is very localized.
12:57
Speaker 2
So that's an example of all the three pieces coming together us being able to model the risk and having it be correlated to revenue and customer knowing that customer education being actually a very short ramp here because in agriculture, they really understand that risk of the business and capital providers being interested in supporting that risk. And then around 2022, we started to get into the parametric reinsurance market.
13:25
Speaker 3
And I would say we were pioneers.
13:27
Speaker 2
We did the first large scale transactions in it.
13:30
Speaker 1
To be clear, reinsurance is the insurance that an insurance company buys.
13:34
Speaker 3
Absolutely.
13:35
Speaker 2
Yes. Yes. Now in parametric reinsurance, your client is not an individual with a house. It is an insurance company with say a hundred thousand houses they cover. The beauty of that is that each one becomes a data point. So as a storm tracks through, as a hurricane tracks through, each point is paying based on storm track and wind speed and a lot of these different factors.
13:59
Speaker 1
So they have the law of large numbers on their side because they're insuring a hundred thousand houses in the hurricane zone or whatever. Exactly.
14:08
Speaker 2
Yeah.
14:09
Speaker 1
Just to be specific, was it hurricane risk in particular? Like you were selling insurance to insurance companies And you paid them if there were a certain number of hurricanes of a certain strength in a certain amount of time, something like that?
14:23
Speaker 3
Yeah, but more structured than that.
14:25
Speaker 2
So every storm that went through, every single data point, i.e. house they covered, would trigger a payout, a small payout, based on where the eye of the storm was, the wind speed, and a few other factors.
14:37
Speaker 1
Oh, I see. So in a way, they're buying reinsurance house by house. Yes.
14:43
Speaker 3
And it's the portfolio.
14:44
Speaker 2
Oh, interesting. structured reinsurance full portfolio and calibrated to their loss history. So not some generic like two hurricanes come and I pay you this much because that doesn't serve the insurer's needs.
14:56
Speaker 3
They need it to be specific. So a regulator will accept that as a valid reinsurance hedge.
15:02
Speaker 1
Oh, interesting. Okay. And that worked.
15:04
Speaker 3
Yes.
15:09
Speaker 1
We'll be back in just a minute. What role does climate change play in your business and in the growth of your business?
15:25
Speaker 3
Great question and comes up a lot.
15:27
Speaker 2
So I always like to say that, like all risks, climate change is a very multi-dimensional problem. Every place has different sensitivity to climate change and every kind of risk has a different level of sensitivity. So if you look at, for example, certain kinds of wildfire risk, yes, have gone.
15:47
Speaker 3
Up tremendously due to climate change.
15:50
Speaker 2
But hurricane risk, if you had to pick a risk that you would say, oh, this is clearly an uptrend in the number of hurricanes hitting Florida or something, you will not see that in the data.
16:01
Speaker 3
And you could go back 100 years, right?
16:03
Speaker 2
Because there are many complicated counterbalancing factors. The other thing that actually is a big counterbalance is that there might be a climate change trend in, say, temperature, especially in the northern latitudes in some places. But the cycles of things like El Nino, La Nina, and NAO, and many other climactic cycles that can last from a few months to a year, often swamp that considerably. And so insurance is written on an annual basis. So if I'm sitting here, overall, climate change does increase volatility of outcomes. in different areas. And your biggest defense is diversification. You want to be writing lots of different lines. And this was actually one of the things that is such a big barrier to entry when you're starting out. A lot of our cohorts who started around that time chose specific lines to write. Like, I'm going to be a wildfire specialist. I'm going to be a hurricane specialist. We consciously chose to build multiple lines all at the same time while being a startup.
17:08
Speaker 3
And it was very difficult. But you needed that to.
17:11
Speaker 2
Escape over-reliance on any one factor. Because yes, volatility is rising in a lot of these risks.
17:19
Speaker 1
I like this big picture idea you're mapping out. And at this moment when you're coming in and that the world is changing faster than the insurance industry is changing and it is getting harder to ensure the risks that people need to ensure. I mean, if we get to now, so, you know, there's the parametric part, like when do you, decide that you need to do more than sell parametric insurance?
17:42
Speaker 2
So we started selling more traditional insurance about a couple years ago. As I mentioned, we were doing parametric reinsurance for property carriers. We ended up acquiring a struggling one and have completely revamped how it operates in terms of better modeling, more efficiency, and many other things.
18:02
Speaker 3
And we have learned a lot across that over time.
18:05
Speaker 1
And specifically, what kinds of insurance are you selling?
18:09
Speaker 3
That was homeowners and commercial in coastal areas.
18:13
Speaker 1
And is coastal areas everywhere in the country or some particular region?
18:18
Speaker 3
East Coast, Gulf, and Hawaii.
18:19
Speaker 1
Uh-huh. So it's basically hurricane risk. Is that the big one there?
18:25
Speaker 3
Yeah. Hurricane risk is a big one.
18:26
Speaker 2
But what we learned through this whole process is how do you work in technology with very experienced insurance professionals? How do you work in AI co-piloting to streamline a regulated entity that has, beyond hurricane risk, a ton of other operational and modeling needs because you're writing the full stack. You're not just writing hurricane coverage. It's not just wind speed. You have to model all sorts of different risks that the customers may be facing and price their own for that.
18:58
Speaker 1
Anything that can happen to your house, more or less.
19:02
Speaker 3
Yes. Or your commercial property.
19:04
Speaker 1
And so are you better at it than big insurance companies that I've heard of? Like, are you just better at modeling risk?
19:13
Speaker 2
Modeling risk is one, I would say, just one of many components that go into it. A lot of the big insurance companies have, I would say, somewhat high cost structures or brittle cost structures. We have brought that down significantly as well. It makes us more nimble. And then finally, also, we avail a wide array of capital providers beyond just traditional reinsurers. You know, what is better is always remains to be seen. When you're managing a risk business, you're only as good as your last, you know, risk.
19:47
Speaker 1
That's fair. So are you saying you can sell policy? cheaper just because you run the business more efficiently and have access to a wider capital pool, and therefore you can sell policies more cheaply and still be profitable?
19:59
Speaker 3
In some cases.
20:00
Speaker 2
And in some cases, what's different about us is, especially there's a lot of regional carriers in these areas, unlike all of those guys, we are also doing in-house climate modeling to compare against the outside models that everybody uses. So we have our own view of risk, we have our outside view of risk, and we can tailor it because we have gone through the pain of building our own modeling and tweaking all the assumptions and knowing, okay, in this case, I trust our model more. Or in this case, I see why the outside vendors are pricing risk this way. And then a lot of it comes down to, remember, as an insurance company, we're not retaining a huge amount of risk. We are retaining some, but we are reinsuring the rest. So if you optimize all three of these components, you can do better than your competition.
20:52
Speaker 1
As I was thinking about your parametric insurance business, I was thinking about prediction markets. And it feels like there is some overlap there. Is there some overlap there?
21:02
Speaker 2
There is.
21:02
Speaker 3
And we are very familiar with these guys. We are very aware. There is an overlap.
21:09
Speaker 2
I would say that the issue, especially with the kinds of risks that we do parametric on, is that because we work with institutions at larger scales, whereas prediction markets are much.
21:20
Speaker 3
More on the retail and smaller ticket size.
21:24
Speaker 2
Yeah. That problem I mentioned in the early days where we spent inordinate amounts of time trying to build distribution. Prediction markets have had a tough time building distribution in these kinds of risks because it takes a lot of effort to find actual hedgers. Prediction markets have not really moved beyond betting. Even if you look at their weather markets, and this is something we've had the discussions with them about, is if you look at their weather markets, the bulk of it is, oh, I'm going to bet on tomorrow's high temperature in New York. That's great from a betting standpoint, but what does that solve for anybody, right? The contracts are not designed for hedging, and they're not designed for institutions to take advantage of, and obviously there's many institutions who also won't really interact with them because of the regulatory uncertainty. Yes. It is hard to overstate how much regulatory constraint exists in these markets. When you're dealing with a utility, there is a huge amount of infrastructure that goes into things like letters of credit and many other things to make sure that they feel comfortable that you'll be around to make that payout. Is a utility going to trust any of these markets yet?
22:42
Speaker 3
I don't think so.
22:43
Speaker 1
Going back to your company, when you think about the kind of medium-term future, what are your main worries? Like if things go wrong, what do you think might go wrong?
22:57
Speaker 2
Well, when you manage a risk business, you always have that aspect of going wrong.
23:02
Speaker 3
Now we reinsure a lot of things.
23:04
Speaker 2
We are also in other markets, we're just arranging the risk, not taking the risk. But you still need capital markets to be around to supply the risk capacity, whether that's reinsurers, alternative capital, or a mix of both. So there's always the worry that some outside event happens that suddenly tightens liquidity incredibly, and that causes some difficulty in arranging these risk pools.
23:33
Speaker 1
Like a financial crisis. You're talking about a financial crisis.
23:36
Speaker 3
Exactly, exactly. Shifting regulatory risks are always a worry.
23:40
Speaker 2
So one of the things that actually led us to get into that coastal insurance business was the law changes that were enacted in Florida. The way things were set up prior was that litigation costs were going out of control. And there's a whole discussion we can have separately, but basically the laws made it very difficult for insurers to essentially deal with the litigation risk that was spiking out of control. So Florida was you know, compared to its percentage of home values insured was much, much, much higher on the litigation percentage. Then reforms were made and those reforms have been excellent and they have brought balance back and actually brought a lot more carriers re-entering the market. So sometimes as you, you know, we're going back again, back to climate risk, climate risk is one component. There are a lot of other social risks that insurers have to bear with And as laws kind of change around this, it can change your risk of litigation or just operational costs.
24:44
Speaker 1
Give me the happy story briefly. I'm going to tell you, I want to save a few minutes for a lightning round. So give me the like one minute happy story.
24:52
Speaker 2
The happy story is that we are, especially with the advent of AI, we are able to scale across more geographies and more types of risks faster and faster, launching more products much more rapidly.
25:07
Speaker 3
And that to me, if you can.
25:10
Speaker 2
Incorporate the AI story with the capital story, you now have a machine that can really start to address these gaps in a much more scalable way.
25:22
Speaker 3
That to me is very, very exciting.
25:28
Speaker 1
We'll be back in a minute with the lightning round. Let's finish with the lightning round. You mentioned in another interview that you spent part of your early childhood in the jungles of southern India where your dad worked for the Forest Service. And I'm curious, what is a memory you have from there? What is something that sticks in your mind?
26:00
Speaker 2
So one memory I had was one of the things he was in charge of was managing a snake park.
26:06
Speaker 1
And so A snake park?
26:09
Speaker 3
Every weekend or two.
26:09
Speaker 1
A snake park?
26:10
Speaker 3
Yeah, a snake park. And I'll get to why.
26:12
Speaker 2
So it's basically a park where they would have giant pits of venomous snakes. And I remember this very starkly as a kid. And basically, the snake venom is used to create anti-venom. And India used to, at least, have one of the highest rates of snake venom deaths in the world. And producing anti-venom was a big deal.
26:32
Speaker 3
So I used to go.
26:32
Speaker 2
There every weekend or every other weekend. I have many memories of seeing these. crazy snakes all over.
26:39
Speaker 1
How do you feel about snakes now?
26:42
Speaker 2
I have a combination of fascination and fear that, you know, I find them fascinating animals. And if you actually look at the structure of snake venom, it is a, they are some of the most interesting chemicals that nature has ever produced. And it's a huge variety of them. So I grew up reading a lot about snakes and stuff, as you might imagine. So anyway, they're fascinating animals, but also quite frightening.
27:12
Speaker 1
What is one thing that running Arbol has taught you about risk?
27:16
Speaker 2
So before I started Arbol, I was in liquid markets. I buy futures contracts on oil. Okay, today things changed. I can sell out of it.
27:28
Speaker 3
Arbol.
27:29
Speaker 2
has been a masterclass on managing risk on so many different levels. One is that the actual risk are both right. Like when you write an insurance contract or when you do a weather derivative, even if you're doing it on behalf of someone else, that risk is very unlikely to be transferable. Once in a while, it can be, but you are stuck with that thing.
27:52
Speaker 1
It's not a product that people are trading all day, every day, like commodities.
27:55
Speaker 2
No. Like we go into this hurricane season with, okay, well, if there's a hurricane, we are going to take losses. There is no getting out of it pretty much, right? So that kind of risk, it makes you a lot sharper with how you model risk, how you price risk and how you structure risk and how much you offload at the beginning of the season so that you're very well covered. And it's a very much greater scale of challenge than to me in liquid markets where you could get out of risk. And then the biggest thing is when you are working inside of a larger institution, a lot of things you don't realize are taken care of by other divisions. Here, you have obviously the regular wildfire, hurricane, crop risk sitting on your head. But then you have legal risk, regulatory risk. You have business strategy risk, like where do you go next? Which products do you invest? You have only a limited amount of capital invested. to spend on building different divisions or different areas. Do you go into emerging markets? Do you go into Europe? Do you go deeper in the US? These are decisions and risks that you have to handle day in and day out, whereas in a larger firm, a lot of things are outsourced to other divisions.
29:17
Speaker 1
Last one. What's one thing you learned working for Ken Griffin at Citadel, the hedge fund? And is he scary? That's really what I want to know. Is he a scary guy?
29:26
Speaker 3
No comment.
29:27
Speaker 2
I actually emailed him recently saying I learned a ton working at Citadel. I learned a lot about process, I would say. that obsession with a clean process and continuous refinement of inefficiencies and blind spots that build up in a company. And he's a master at kind of being on top of details that are just Unbelievable. For a man who manages his scale of businesses, the amount of detail he can navigate within each mini area of the company is very impressive. And I learned a lot on that aspect, like just how many process failures you can avoid by just being so utterly focused on all these details.
30:25
Speaker 1
I know you got to go. Thank you for your time.
30:28
Speaker 3
I appreciate it. This was fun.
30:38
Speaker 1
Sid Jha is the founder and CEO of Arbol. One quick note, we're going to be taking a break for a couple of weeks after this show, but we'll be back soon. Today's show was produced by Gabriel Hunter Chang, engineered by Sarah Bruguier, and our showrunner and editor is Jake Harper. I'm Jacob Goldstein.
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