[00:00:02.930] – Alex Serman

Welcome to this episode of Whiskey and WealthTech. I’m Alex Serman, the Managing Director of Wealth here at First Rate. Joining me today is Ben Webster of OWL ESG. Welcome, Ben. Happy to have you on the podcast.

[00:00:15.110] – Ben Webster

Thanks for having me, Alex. I’m excited to talk all things ESG.

[00:00:19.890] – Alex Serman

Perfect.

[00:00:20.550] – Ben Webster

We can’t forget talking about bourbon, right. Whiskey and all that stuff.

[00:00:26.940] – Ben Webster

Absolutely. So could you give us a brief introduction about yourself and about OWL ESG?

[00:00:32.810] – Ben Webster

Yeah, a little bit about myself. Born and raised in California, Los Angeles, specifically. Been in the finance industry in one way or another for most of my career, even though my background was in my degree, was in physics, did worked a lot with hedge funds, private equity funds, and other financial product issuers to raise capital for a good chunk of my career. And a little over a decade ago, I went on this ESG journey with my partner, co founder Andrew Smith, and we started out and good. Ten plus years of building a company and learning how to be a better business person and service customers better. And we’re here today, and the company is still growing, and I hope to keep that happening.

[00:01:32.670] – Alex Serman

Excellent. Well, before we get too far into the episode, let’s crack open some whiskey. And today we’ll be drinking the Westland American Single Malt out of Seattle, Washington. So we’re both able to get that at our local liquor stores here, but let’s dive right in.

[00:01:54.650] – Ben Webster

All right. I guess we’re just going to take a drink.

[00:01:58.480] – Alex Serman

Yeah.

[00:02:00.950] – Ben Webster

Are we supposed to finish it?

[00:02:03.190] – Ben Webster

Or should we savor it gently over time?

[00:02:06.230] – Alex Serman

I usually say however you want to drink it, that’s your business. But I tend to savor it because otherwise I’ll be coughing here on screen.

[00:02:13.900] – Ben Webster

Yeah.

[00:02:14.190] – Ben Webster

Well, you were telling me that you are a whiskey aficionado. Though I have drank many a whiskey over my time, I wouldn’t call myself an aficionado. What made you choose this one?

[00:02:30.400] – Alex Serman

So this one is really interesting, so I thought it would be great for a topic around ESG, because Westland does an incredible job about being transparent, kind of like too much so that it’s going to typically bore your average drinker if you’re not a big whiskey nerd like I am. And so you go to their website, it’ll tell you everything you need to know about this whiskey. What yeast they’re using, where the barley came from, where their water sources, size of their still. I mean, it is extremely transparent. And that’s a big issue in the whiskey industry, is the lack of transparency for a lot of firms. So this is something I really appreciate about Westland, is that they go above and beyond to tell you exactly what’s going into that bottle and what product you’re buying. Whereas there’s other distilleries that if you just look on the back and instead of it saying being distilled by, or if it just says bottled by or anything like that, you know that that distillery didn’t actually make that whiskey. And they’re not telling you where it’s coming from.

[00:03:35.210] – Ben Webster

Got it. I can appreciate, as someone, whether you’re a drinker of whiskey or not, I can appreciate being able to understand where the ingredients come from so that, you know, with confidence and trust that the ingredients are hopefully, in this case, high quality.

[00:04:00.130] – Alex Serman

Right.

[00:04:01.790] – Ben Webster

And that’s the key. When you’re amalgamating something or creating a product that’s based on a lot of other items and ingredients, it could look good. It could potentially somewhat taste.

[00:04:16.570] – Ben Webster

Okay.

[00:04:17.360] – Ben Webster

But you may be imbibing stuff that’s just really bad, really low quality. But that said, other than the transparency, is there anything else about this whiskey that really stands out in your mind compared to, like, others that you may also like?

[00:04:37.850] – Alex Serman

So, to me, this is an American single malt, and they add a little bit of peat to this. It’s all barley, and it really reminds me of a good Highland Scotch. So not quite a spaceide like your McAllen’s or whiskeys like that that are really fruity and sweet. Like this one. It’s got a little bit of earthiness, a little bit of not a ton of smoke. A little bit, but it just really I don’t know, it feels like it’s not trying to appeal to that really sweet part of your palate, but kind of gives a little bit more depth and character to it than you might find from some other single month.

[00:05:21.590] – Ben Webster

So for all of those watching today, we want to make sure everyone knows that we are not sponsored by Westland. That said, anyone from Westland who’s listening, there are open sponsorships for the Whiskey and WealthTech podcast. And so your inquiry should come into Alex Serman and perhaps we can collaborate.

[00:05:40.430] – Alex Serman

Absolutely.

[00:05:42.030] – Alex Serman

We aren’t sponsored by any of these whiskeys, but would be happy to get some sponsorships here in the future. But so far, my only complaint about Westland is that the bottles are really hard to open.

[00:05:54.320] – Ben Webster

Yes, but we can compensate for that if you can send us a free case. Westland thank you.

[00:06:02.130] – Alex Serman

That’s awesome. Well, glad we’re enjoying this and so kind of jumping off the transparency and being able to appreciate where your ingredients are coming from. So I think that directly correlates with some of the challenges that we’re seeing in ESG and the ratings. So, Ben, would you be able to. Speak to that about kind of what are some of those challenges and what are you doing to help address those without?

[00:06:30.350] – Ben Webster

So we’re kind of entering, I would say, the fourth generation of ESG right now. And if you were looking at the generations, one of the generations, the first generation, that kind of has been around for a long time, back to the Quakers and even back to hundreds of years ago with the dutch East Indies companies and what have you. You could see in the historical record that there has been always, as far as we can tell, investors that want to vote their ethical values right? For example, staying away from certain lines of business that may not meet what their values are looking. For example, I’m not judging any type of activity, but some people may or may not want to invest in alcohol, right? Some people may or may not want to invest in tobacco companies. And I’m not saying whether those activities are wrong or right. Each person has to make that decision for themselves. But that first generation of what I’m labeling here as ESG, but back then, what’s considered more of socially responsible investing was essentially trying to stay away from companies that were engaged in business activities that may be perfectly legal but didn’t meet their specific values, right? Let’s say maybe about 15 years ago, 15 to 20 years ago, this next generation of ESG that we’re all becoming more familiar with started to make headway. And this next generation of ESG is using ESG without see more of an ESG integration approach where ESG has material consequences. How well a company is managing their ESG risks and their ESG opportunities has material consequences for how you may manage money and the risk and return that you may generate. The way that generation of ESG expressed itself was in ESG ratings. And the reason why you need ESG ratings is because they’re easy to consume, they’re normalized. You can apply them to your portfolio pretty simply, and then once you’ve applied them to at least the individual securities or your universe that you’re looking at, then it was a much quicker starting off point from which to do maybe any alpha research or risk mitigation research or even just portfolio optimization to stay away from companies that may have bad ESG practices or put more money in companies with better ESG practices. The reason why ratings were so important, again, going back to that simplicity, the ESG disclosures, and this is where the problem really rears its ugly head is for the most part, ESG disclosures are not regulated.

[00:09:38.910] – Ben Webster

They’re starting to become regulated in Europe. And the door is opening here in the U.S. where the SEC is considering certain regulations. But at the end of the day, there is no standardized reporting, very little standardized reporting. There’s very little regulated reporting. It’s unstructured. So it’s very, very hard to gather this data because no two companies reporting in the same way, they’re not necessarily reporting on the same metrics. And even if they are reporting them reporting on the same metrics, they’re reporting them in different ways. An example could be this is our scope one carbon emissions. Another company can go, our goals are to reduce scope one carbon emissions by 40%, right? They’re different things and they’re not reported in the same way. What ratings did was provide companies a valuable service. That service was, we’re going to go delve into all that chaos. We’re going to delve into this unstandardized, unstructured data jungle and we’re going to analyze it, we’re going to research it, we’re going to distill it down into the essence of good or bad or grades of good or bad and made it easy to consume.

[00:10:58.710] – Ben Webster

It took the hard work away from investors who were either not qualified, didn’t have the skills, or just didn’t want to go in and do all that because it’s very hard to do. That was the second generation. And ESG ratings still are a big part of this business. But the next generation, what are called a third generation, the third generation was, okay, let’s take ratings, right? And let’s insert them into financial technology platforms and not only make it easy with ratings, but let’s make it easy because we’re going to do all the mapping for you. We’re going to give you great point and click tools to evaluate your portfolio, compare companies versus each other, what have you. And that was that next generation. And it’s valuable because it makes things easy for the end clients. The problem is that there still exists major issues with the ratings. And even if you’re looking at the raw data, there’s still major issues that exist in the raw data and simply put, for the ratings. And there’s a lot of research out there to support this. Some amazing white papers by a collaborator of ours called Florian Berg, for example, who wrote a paper on the Aggregate Confusion Project, which is comparing ratings versus different providers.

[00:12:33.580] – Ben Webster

And they’re finding that there’s a huge dispersion from different ratings providers. Said another way, one ratings provider can give Tesla a great score on E, another ratings provider can give a terrible score on E and everything in between because they have a different way of looking at all that raw data that’s published and they synthesize it in a different way and come to different conclusions, right? So it’s well known that ratings are subjective. What’s not as well known, and it’s starting to become more well known, is that the raw data powering ratings also has significant issues. For example, it’s very time decade. So a lot of the major ratings providers, they’re creating a rating and a rating system that is subjective and it’s different from the other rating providers systems. As in the dispersion of EC ratings, the data powering them is different. One vendor could say two women are on the board. Another vendor could say three women are on the board. One vendor could say the scope, one carbon emissions are 1572 tons metric tons per year. Another provider could say, no, it’s 2250 metric tons per year. And the reason for that is not necessarily because they are doing a bad job collecting the data.

[00:13:53.610] – Ben Webster

Sometimes they are, but more often than not, it’s because of time decay. They’re gathering that data every 21 to 30 months on average.

[00:14:02.950] – Alex Serman

Right.

[00:14:03.820] – Ben Webster

And so what that means is not only are the ratings subjective, but if you are licensing the raw data, you’re often licensing the raw data that is, over one year, oftentimes two years time decayed, and therefore inaccurate because it’s outdated data. These two things – we’re trying to solve the subjectivity of the ratings. One of the things that Al has been working on for many years, that was in our traditional project products called the product called the Al ESG Consensus Boards. But our next generation product is what’s called the Al ESG IQ data, which is we gather hundreds of raw ESG data points, but where the other providers are gathering every 21 to 30 months and therefore have accuracy below 30%, we’re gathering right now every six months, and by the end of the year, we’ll be gathering quarterly. So time decay is minuscule, and our accuracy maintains above a 97% level at all times. So that’s some of the things we’re doing to raise the standard of ESG data and provide better data to the market. That was a long explanation, but hopefully it gave a kind of great context to what’s going on in the industry.

[00:15:23.850] – Alex Serman

Absolutely. Yeah. And regulation, I think, will help mitigate some of that in the future. But even with that time decay stuff, you can’t invest based off of two year old information and expect it to be valuable to you. Today, you’re trying to optimize your portfolio. You need more real time information for that. And so you mentioned you’re helping mitigate that by collecting data on a much more frequent basis, and you’ve been working with First Rate to help achieve that. But can you talk a little bit more about how you’re working with First Rate and how our teams have been able to assist you and the OWL ESG firm as a whole with what you’re doing?

[00:16:08.580] – Ben Webster

Yeah. So let’s take a step back, and I want to talk about how ESG data is traditionally gathered right by the major firms in the industry. Typically, they have large teams of analysts, usually overseas, to keep costs down, and they are manually gathering data. They’ll have two screens open. On one screen, they’ll be going through a sustainability port or an annual port, and another screen will be an Excel spreadsheet. And they’ll be like, okay, I’m looking at Tesla. Okay, this is Tesla scope on carbon. This is Tesla’s gender pay gap. Let me put it over here. Assuming all those are disclosed on right, it’s a very manually intensive, time consuming, error prone process.

[00:17:03.510] – Ben Webster

In order to scale effectively, you have to have very defined guidelines, and you have to train everybody up on those guidelines. And it’s very hard to change course that introduce new types of metrics or new ways of looking right. So translate. It’s time consuming, it’s error prone. It’s costly. And as a result, that’s where the 21 to 30 months time frame comes from. Some data points they gather more frequently than that, don’t get me wrong. But on average, that’s what it is, 21 to 30 months. And each of the docs they’re going through to add a little more color can be often be hundreds of pages long. So what often happens is they miss data that’s in there because those documents are just so large and expensive. So not only are they gathering sometimes data inaccurately, they’re missing swaths of data. And so that’s just a problem and how you gather data. What Al has been able to do is build AI machine learning tools, technology tools, to gather that data cost effectively, more efficiently, more frequently, and with less error, right? That technology stack that we’ve built, we’ve worked with First Rate to build that.

[00:18:29.640] – Ben Webster

Now, the way we work with First Rate to build that is that First Rate, and you know this, right, has what you call the BOT model (build, operate, transfer model). And essentially what it is is that First Rate has overseas teams, specifically in India, where they can help recruit overseas talent. So imagine Al, we’re still a small company, but we have to compete with Google and Microsoft and Amazon to recruit software engineers, data analysts, data scientists. And the reason why we want to do it overseas, because it is more cost effective. And you have amazing talent over there. But in order to recruit them, you need to have a presence in those markets. You need to have a company that’s set up. You need to have the legal infrastructure to pay them, to pay taxes. You need to have that presence there that’s known to attract talent, right? You need to have relationships that are built there, that have been built over years and years and years to do all this effectively. So what First Rate has enabled us to do is scale up our team overseas with extremely talented people that are 100% dedicated to although they technically work for first rate under the envelope of First Rate India legal infrastructure, they are 100% dedicated to Al.

[00:19:58.030] – Ben Webster

They have options, and so they’re vested in ownership in Al. Ultimately, we pay for their salaries and their benefits and what have you. And they are our team. And that team, with our US team together collaborate to build our software applications to maintain our AI technology and all of that. It’s been a wonderful relationship that has, how do I say it? Helped us scale what we’re doing much more efficiently and cost effectively.

[00:20:32.890] – Alex Serman

Absolutely. Yeah, definitely. Talent is rampant over there, and it is difficult to lock it down because you are competing with such massive giants in the software space. And so that BOT model is really great to be able to help scale up development teams, get people trained and do it in a way that really benefits and allows smaller firms like ours to really have that differentiating edge and.

[00:21:06.150] – Ben Webster

Be able to recruit that I know you’re working with successfully with other clients to do the same. And it’s a great approach and it’s been a beneficial doubt. I think I’ve been remiss on my whiskey drinking. I apologize.

[00:21:21.850] – Alex Serman

You’re great. Well, you talked with a colleague of mine, Marshall Smith, a few months ago back in August on his Ventures in WealthTech podcast and so loved that episode. Could you give us a little bit of an update on just what’s changed with you since then? What’s changed with OWL? How over the last six months or so, have you guys really progressed and taking steps forward?

[00:21:48.290] – Ben Webster

Yeah, it’s a great question. I think what’s progressed is that we’ve built this amazing technology that we use for ourselves to gather data, effective. And part of that technology is tying in the AI machine learning world, it’s called ‘humans in the loop’. How do I say it? Both quality control the output, but also to give that feedback loop. That system improved machine learning the result of that. And so at that time, our goal had been really focused on becoming what we’ll say called the gold standard of ESG data. To reiterate, current data is time decayed, therefore inaccurate. There’s also no data providence.

[00:22:45.240] – Alex Serman

Right.

[00:22:45.700] – Ben Webster

You can get a data point again, 2250 metric tons of carbon emissions, and you have no idea where that data point came from. Did you get it from a sustainability report? Did you get it from a CDP report? Did you get it from the website? Where did you get that data from? And a lot of data in the industry is modeled, so you may be getting that data point from another provider. And for all you know, it’s not a data point that was disclosed, but they ran was a data point that wasn’t disclosed and they ran some regression and analysis against their industry peers and created that number. Right. And so the problems we were trying to solve was, hey, we’re going to give you accurate data that’s up to date, and you can check the data provenance so you can verify that the data is accurate and you know exactly where it came from.

[00:23:35.060] – Alex Serman

Right.

[00:23:35.860] – Ben Webster

What’s changed is that at that time, we were just trying to be a data provider and give you the best data in the industry, which alone is I think it’s an awesome goal. But what’s changed since then is that’s no longer the goal to be the best data provider. That’s the foundation. That’s the first step. The next step is layering on applications onto that foundation. We’re launching essentially what we call the deep research app here. But think about what’s going on with ChatGPT now. Everybody’s been hearing about AI this, AI that, and the reason why everyone’s talking about it so much today is that OpenAI. When they put ChatGPT, they put a user interface on it that was accessible to anyone. Like my twelve year old kid son has gone on and used ChatGPT. He doesn’t turn in book reports, but to write things and generate content. And it looks professionally done. Like wow. And he did that by putting in a question in the ChatGPT.

[00:24:54.070] – Alex Serman

Right.

[00:24:54.420] – Ben Webster

Or said, find this. He loves Rocket League, it’s a video game. And he said, tell me the best Rocket League strategy so I can become a diamond. Which is one of the rankings. And it spits out all this stuff and it’s like, wow, that’s actually quite good and accurate. That’s what we’re doing with ESG. We are turning the technology that we use to gather ESG data and we’re, we’re opening that up to the to end clients.

[00:25:23.520] – Alex Serman

Right.

[00:25:24.020] – Ben Webster

We’re opening up that to sustainability research teams, sustainability teams. We’re opening that up to stewardship teams that are engaging with kind of companies voting proxy. We’re opening it up to investors who are building financial products that are differentiated because they’re ESG experts. Right. And they’re tired of the time decay data, inaccurate data, and they decide that they want to gather it themselves. But instead of doing it manually, now they have a tool like ours to do it in an automated fashion. We’re turning it to corporate consultants that are consulting with corporates and helping them, helping those corporate corporations, corporate issuers benchmark themselves against peers to make sure that the EC data that they are analyzing and taking action upon is accurate.

[00:26:22.030] – Ben Webster

A lot of this process of how those user groups are using ESG data is manually driven. They’re gathering data on their own. They’re cross checking the data from their existing providers because they know it’s inaccurate. They want to build portfolio strategies out of it. But again, they’ve decided to go directly to the raw data themselves because they can’t trust the data from other providers. So a lot of that takes some days, weeks, and sometimes months of manual time, analysts who have to be deep ESG experts who are dealing with complicated data sets and what have you. And they’re spending all that time to prepare the data to do what they want. Well, we’re now taking what sometimes takes sometimes hours, but oftentimes weeks and months. And we’re providing them the tools and applications to do it, oftentimes in minutes.

[00:27:28.540] – Alex Serman

Right.

[00:27:29.790] – Ben Webster

To gather data on their own, cross check data, apply it to peers and portfolios. And so with what I said, the foundation of the best data in the industry, that’s kind of the next stage of what we’ve been doing.

[00:27:45.750] – Alex Serman

Excellent. That sounds like you’ve got a really good handle on kind of what this industry needs, how it’s moving forward. I think you put it rightly that being the gold standard of data ratings is good, but that’s the foundation to just build from there and to continue to improve, provide information to the industry and make sure that investors and firms are informed of what’s going on and that they have all those tools and all that information readily accessible to make those right decisions.

[00:28:21.710] – Ben Webster

Cheers to that. We could do a virtual cheers here. We clarify. It’s not just the ratings, it’s the raw data that’s the foundation. Right? Yeah. If you look at the spend on ESG data, the spend on analysts to deal with bad ESG data is like five X to spend on ESG data. And that five X is expected to grow four X over the next few years to over $20 billion annually. So without we can go in there and we can give you just better data. But what more importantly that we can do is you have ten analysts dealing with bad data now and just trying to figure out how to make the bad data better. So you can use it. Well, we’re going to come in there, we can sell you the data, but we can also sell you the tools. You only need one or two analysts to do the job of ten and they can do it in a fraction of the time at a fraction of the cost with a much higher quality output. It takes those ten analysts and now one or two analysts can do the job and the rest of the analysts can focus on actually doing stuff that’s going to be alpha generating. And it’s not just investors, it’s corporate issuers and their consultants that are revenue generating, that are additive to building your business rather than figuring out how to get to the starting line because the data is bad. So you got to get to the starting line of making sure somehow this data is good and usable.

[00:30:10.130] – Ben Webster

And so especially in these markets when people are going to be very cost sensitive, less companies are going to buy because less companies want to add to their ad cost at this point in time. Al is a cost reducer. In a way, if you think about it, we’re an ESG productivity and efficiency company in a way. That’s where we think the exponential benefit of what we do that no other provider in the market can do.

[00:30:45.610] – Alex Serman

Well, that sounds wonderful. And I know that you’re currently working with, with a lot of great firms on helping them do this, hoping that you continue to find success and continue to build on this foundation that you’ve built. And so, Ben, thank you so much for your time today. I think this was a wonderful chat, wonderful whiskey, and really fitting for understanding where your data comes from, where your whiskey comes from, how it’s made up. And you can’t fake a good product.

[00:31:21.290] – Ben Webster

Yeah, that’s true. And Westland, if you’re listening, you can contact us and we’ll give you Alex’s address to send case to him for him to promote you even more. Thank you.

[00:31:39.640] – Alex Serman

Cheers. Well, thanks, Ben, and thanks for tuning in. And we’ll see you next time on Whiskey & WealthTech.

[00:31:44.960] – Ben Webster

Thanks, everybody. Appreciate you joining. Bye.