← Alt Goes Mainstream: The Latest on Alternative Investments, WealthTech, & Private Markets
Alt Goes Mainstream: The Latest on Alternative Investments, WealthTech, & Private Markets
73 Strings' Yann Magnan - unlocking valuation intelligence in private markets
00:44:16
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- [00:00]
Yan Magnan
At 73 strings. We actually have been using AI since day one, mid 2020, since we started the business. But AI at that point in time, as you rightly pointed out, was a different type of AI. We're using machine learning and natural language processing still algos. So what we've seen is that these algos have improved dramatically in the past few years, and they will continue to improve dramatically. So it's a question of continuing to embed this technology and basically continuing to add efficiencies into these platforms that you can basically push to your cl.
- [00:32]
Podcast Host (Intro/Outro Voice)
Everybody's going to eat. We're going mainstream. All my family see you on mainstream. We're going mainstream.
- [00:46]
Podcast Narrator/Producer
From Wall street to Melrose Avenue, we're going mainstream. Venture capitalists to athletes to creators to the person who is collecting trading cards, we're going mainstream. And a collision of culture and finance,
- [01:02]
Michael (Podcast Interviewer)
we're going Mainstre this episode of Altgoes
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Podcast Narrator/Producer
Mainstream is brought to you by Altimus, the full service fund administrator and transfer agent powering asset managers in private and public markets. As alts go mainstream, you need real expertise to handle complex fund structures, connect with key distribution partners, and handle sophisticated compliance reporting and transparency demands. That's Altimus High Tech High Touch Solutions for over 450 clients and 2,500 funds with over $775 billion in assets under administration. Backed by an expert team of over 1200 employees, they place client service at the core of their business, helping you navigate complexity during your fund structuring or launch, and then supporting you through every stage of growth. Whether you're already in the market or thinking about entering private wealth. You can trust their team's deep expertise in retail alternatives to help you reach your goals. Learn more at ultimusfundsolutions.com or email infoultimistfundsolutions.com welcome back to the Alcos Mainstream Podcast.
- [02:03]
Michael (Podcast Interviewer)
Today's episode is with a founder who
- [02:05]
Podcast Narrator/Producer
is building mission critical valuation and portfolio monitoring software for alternative asset managers. We're joined by Yan Magnan, the co founder and CEO of 73 Strings, to discuss how valuation work and portfolio monitoring is moving from manual to automated and why that's so important for the industry. 73 Strings has leveraged AI and automation to more seamlessly and cost effectively extract data, monitor portfolios and streamline middle office processes. Proceeds for valuations 73 strings Works with a number of the industry's top alternative asset managers and has received investment from Blackstone Growth Equity at Goldman Sachs Alternatives, Hamilton Lane Golub Fidelity International Strategic Ventures and Broadhaven Ventures, amongst others. Yan has brought his experience as a senior member of the Duff and Phelps team, where he was EMEA Market Leader and member of the Global Operating Committee, and as a partner at EY's Transaction Advisory Services to help bring valuation and portfolio monitoring solutions to into the mainstream. Yan and I had a fascinating conversation about how technology, innovation and AI are impacting private markets and perspectives on valuation work today. Thanks Yan for coming on the show to share your expertise, insights and passion about private markets, collision of culture and finance.
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Podcast Host (Intro/Outro Voice)
We're going mainstream.
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Michael (Podcast Interviewer)
Yan, welcome to the ALOS Mainstream Podcast.
- [03:18]
Yan Magnan
Michael, very happy to be here with you today.
- [03:21]
Michael (Podcast Interviewer)
Pleasure to have you back and you were on the podcast about a year ago. A lot has changed in the world of private markets. A lot has changed in the world of valuations. I want to get to all of that and I think it's a really important time to be talking about things as it relates to post investment in private markets, evergreen funds, valuations, more transparency around valuation. All those things are things you're doing and those are top of mind for both GPs and LPs right now. First though, I want to just ground the conversation in your background. How did you get to where you are today and maybe if you could also share the evolution in the way valuation and portfolio monitoring have works. I think that's emblematic of where we are in private markets. You did things manually, now you're doing them in an automated way, so would love to start there.
- [04:12]
Yan Magnan
I started my career 25 years ago, started my career as a corporate finance and valuation consultant at first at ey before in France when I moved to a US consultancy called at that point in time Defend Theps and now known by the name of Kroll as you rightly pointed out. Everything that I was doing at that point in time in the early days, everything that I was overseeing my teams doing back a few years later and then everything that I was seeing my clients doing at that point in time as well, everything was when it comes to valuation of non listed assets, everything was manual. Manual as in Google Search, Excel and email. As a person I'm fairly nervous and I like efficiency and I was thinking that does not really work. Excel, Google Search, email, think like 2015, 2020 18, 2020. You start hearing about the cloud industry, you start hearing about Genai and AI to start with and you're just thinking there must be ways to do things differently, there must be ways to create efficiencies and there must be ways to do valuation in a framework that is governed and auditable and traceable, so that at the end of the day, you can develop this valuation in the best possible way, in the fastest possible way, in the most structured and auditable and traceable type of way. So with that as an idea and as a vision, with a few of my colleagues in 2020, we started 73 strings. And the play was, the idea was let's develop the platforms. Actually we have two. One that covers equity instruments and the other one that covers credit instruments. Different valuation methodologies. So let's create platforms that will basically facilitate the evaluation work, that will create that governed and structured framework that the managers will be able to use so that they can continue to grow and pretty fast. As you know, the industry has been growing what, 10, 15% year over year, I would say the ads industry at large. So enable these industry, these managers to grow and support their valuation processes and the middle of these processes in a way that is scalable for them. We started in the summer 2020. We've had a pretty nice ride since then. And we've seen something happen actually. And we've had that conversation quite a few times, you and I. We've seen something happen in the past 12 months, or I mean, it started a bit earlier than that, I would say two years ago. But really in the past 12 months what we've seen happen is that on top of the growth of the industry, we've also seen the trend towards evergreen funds and private capital GPs trying to attract retail investors into their capital. We've seen that accelerate dramatically in the past year. And that creates a lot of new challenges for these managers on multiple fronts, not just on valuation and middle office, but in particular when it comes to middle office and valuation. Because suddenly you have people, you and me, that invest into these funds. And we are very happy to do that. We are very happy to be able to invest capital in an industry that generates significant return as long as you pick the managers appropriately. But the thing is that when we do that, we want to make sure that we can do some arbitrage in our portfolio. We want to make sure that we can enter in this type of funds almost at any point in time. We want to make sure quite often that we want to exit as well as we have seen lately, almost at any point in time. And that changes a lot the way our clients are basically operating. Because you're not anymore in that close ended fund where capital comes in and capital comes out at the end of the fund. You're in that environment where transactions are happening across the life of the fund. And it's not just that these valuations are being used for reporting, by the way, these valuations are being used for transactions. So that creates another challenge to our clients.
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Michael (Podcast Interviewer)
A number of interesting points that I want to unpack. But on the last point that you just made, clients are using these for transactions both in terms of trying to make sense of maybe they need to sell an asset if it's, particularly if it's in an evergreen, because they need to be able to continue to season that portfolio, add new assets to the portfolio, exit other assets. You have the growth of not just evergreens, but of continuation vehicles. How do you think about the importance of valuations today relative to the private capital industry? When you were in IT at Kroll or Duff and Phelps, et cetera? Are there things that have really changed about how both GPs and LPs are thinking about valuations and how they think about doing them?
- [08:41]
Yan Magnan
Dramatically, actually. So back a few years ago, valuation was mostly reporting exercise, a very important one. You want to make sure that your institutional LPs get a robust reporting every time that they want this robust reporting, typically quarterly basis. But what has changed with the trends towards Italy investors and evergreen funds is that people are suddenly transacting on these valuations. And when they are transacting on these valuations, actually they are doing two things. They want to sell and exit. But they want to sell and exit comparing and understanding what the value of their illiquid holdings as compared to the value of their liquid holdings. So they are comparing both. And so what that means is that we are moving from a world where valuation of non listed assets were very isolated, they were reporting information into a world where visualizations need to resemble and to mimic as close as possible the public world. It's very interesting because when we speak to clients about evergreen and retail, the first question is about technology and creating efficiency. And that's true, that's a very important one. But the second question, very important as well, is that the philosophy that you are applying to develop these valuations is very, very different as well. You have to be much closer how the market operates. Because if you don't, and if you create a valuation that is theoretical, maybe slightly on the more cautious side of things, you as a manager take the risk that some of your retail investors are going to come to you and tell you, well, I don't understand. I transacted on this valuation based on information you provided me with. But actually it might have been slightly biased, not wrong, but slightly on the more cautious side of things. And if you had told me that it was not the case, I would maybe have taken a different decision. So the entire philosophy is also changing.
- [10:28]
Michael (Podcast Interviewer)
When I hear you talk about that, where my mind goes is you're taking a back office process and it actually so post trade or post investment, it actually feeds into pre trade or pre investment. Because to your point, there's new investors coming into an evergreen fund at a certain point in time when they strike a nav. There's existing investors who may want to invest more, there's existing investors who may want to redeem some. There's gps who may need to figure out how to continue to manage that portfolio. So it's almost as if that the back office is becoming part of the front office as it relates to how you understand value market and then ultimately distribute these evergreen funds.
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Yan Magnan
Yeah, I mean, depends how you define front office. In my world, typically front office is the investment team. They invest and they exit. But if you think about the gp, as you would probably not contradict me, one of the key functions of a GP is actually to ask a. And if you look at it from that perspective, to raise and invest the capital. But starting with raising the capital, and you start from that perspective, you have a new constituent, a new group of stakeholders that are not the typical institutional LPs that have certain ways of looking at things and certain ways of thinking at things. You have a different group with very different ways of thinking at things and looking at things. And you have to balance both. And that's a very different exercise.
- [11:50]
Michael (Podcast Interviewer)
You talk about this being a different exercise. What exactly is different about it? And what skills or tools do gps need to have to be able to do that properly?
- [11:59]
Yan Magnan
Until recently, private capital was supposed to be private. And it is private. It's like these assets are not traded. Why would we get to a value that would mimic anything that's public? Well, the reason is that because now you have investors that expect you to do that, otherwise they can't really transact. And that's what's changed a lot in the past year.
- [12:17]
Michael (Podcast Interviewer)
From a philosophical perspective though, it brings up an interesting nuance to the point that you just made, which is it's great that there's more transparency. I think we can all agree on that. There needs to be both from a regulatory perspective and from a vehicle structure perspective, particularly as you're dealing with evergreen funds. But from a philosophical perspective, if you make these funds and these investments more transparent, then there's the possibility that there's more price discovery and that there is more, quote, unquote, liquidity or potential for liquidity. I want to be very clear just to make one footnote to that, which is that I don't believe these vehicles should be called semi liquid. So when I say liquidity or potential liquidity, what I mean is in the sense that there's a possibility, as you create transparency in this market with illiquid assets, you create the possibility for a more functioning secondary market and more frequent changing of hands of assets. Just from a philosophical perspective, how do you think about that? And is that a good thing for private markets? Is it a not so good thing? Because I think there has been the case where the fact that assets were illiquid meant that people had to be patient.
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Yan Magnan
There's plenty of businesses out there that need capital to continue to grow. They can tap public markets for that, but actually that's not happening that often. So the next potential pool of capital that they can tap is actually the private industry capital. And that's a very, very important function on the marketplace. There's plenty of these businesses to finance, plenty of very, very good businesses. If you want to get more capital to finance these very, very good businesses, you have to find ways to do it. And the reality is that retail investors have capital that they can and sometimes they want to invest into this industry. And basically the flip side of that is that you have to accept that to get this capital in there, there is to be some kind of liquidity. So I don't know. I'm not answering the question, but I'm just saying it's part of the way the economy is going. If you want the economy to grow and to grow fast, and I think we all want that, at some point in time, you have to put capital to work. And it can't just be public capital, it will be private capital as well. So that would create more liquidity. Yes, that would create more transparency. Yes. I do think. Personally, I think it's a good thing, but I understand it can be debatable.
- [14:49]
Michael (Podcast Interviewer)
There's people on both sides, some who would say illiquidity is a feature, some who would say illiquidity is a bug. And there's merits to both of those arguments and both of those points. I think on the point about transparency, I think we can probably all agree that particularly for Evergreen funds, there should be more transparency, as there's more frequent reporting. As there has to be more frequent reporting. What is different about the way in which the valuation process works with Evergreen Funds than with closed end funds? Because the industry has to make a change, particularly for those firms that run and manage these evergreen funds. They may have to do things differently as it relates to what they need from an operational perspective. What is different about how these firms are going about creating the resources and infrastructure to do these valuations properly?
- [15:43]
Yan Magnan
We're talking about the evergreen funds and the non evergreen funds, but at the end of the day, it's the same portfolio companies in the background, exactly the same. And that's very important because what that means is that anyway, again we're getting back to how things portfolio companies are financed, but might be financed by a pool of what you call private, private capital, institutional LPs, but they might be financed as well by evergreen type of structure that is retained investors. And you have to balance both. What's different is that again, back to the evergreen structure. You have to have more transparency, you have to have higher frequency in terms of the reporting process in general and valuation as well. As a matter of fact, you have to have higher transparency, you have to have better robustness and higher effectiveness of the evaluation process. So all of that has to happen. And here is the thing, is that at the end of the day, from my standpoint, everything that's happening on the evergreen side of things is transpiring to the private side of things. Because like I said, it's the same portfolio company at the end of the day. And what I think we'll be seeing is that the industry will align to best practices or the highest denominator, I would say, which is likely going to be the evergreen type of process. Evergreen also is going to require probably a higher set of regulation again, because we are back to the fact that retail investors, and I was reading yesterday on my way from London to New York that the 401k plans are quite likely going to be open to retail investors. All of that means that at the end of the day there will be more regulation that applies to the industry.
- [17:14]
Michael (Podcast Interviewer)
Could the process of monitoring and valuing assets in evergreen structures be done without the technology that is available to firms today?
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Yan Magnan
Could it be done? Yes, the answer is yes. It's been done for like, you know, 40 years with Excel, Google Search and email. Or maybe not Google search, but it's been done for a long time. The key question is, is that an efficient way to do things? And then there the answer is no. As the industry is growing, as a frequency is increasing, you want to have a very robust process, you want to have a very consistent process. And it does not make sense if there is A strong set of technology solutions that can enable that work to continue to do that work manually because just it's a massive and massively costly effort that has to be done.
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Michael (Podcast Interviewer)
Where does technology give firms the most leverage?
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Yan Magnan
Collecting data, structuring data, creating consistency, and doing that in a governed, auditable, traceable type of environment. That's what matters most for this industry, for this part of the process. And again, because at the end of the day, you're dealing with a process that is not regulated in the sense that we are thinking about regulation with public markets, but that has a lot of consequences and you need to make sure that you're right. So everything that's on how you structure data consistently and create that governed environment is the most critical part of things.
- [18:37]
Michael (Podcast Interviewer)
What's required for firms to be able to do that? Well, do they need to have enough resources internally? Do they need to spend enough for a certain amount of money? How and what will be the ingredients to success for these firms that have to manage particularly evergreen vehicles?
- [18:53]
Yan Magnan
We have to have the expertise, generally speaking, and the expertise. You either have that with people or you can have a combination of people and technology. A lot of these processes are codable. They can be thought through and developed in a way that most of what a human would know can be embedded into a technology. And then you leave to human whatever is the most significant part of the process, which is human judgment asserting when there are choices to be done, how
- [19:20]
Michael (Podcast Interviewer)
to do these choices, what still needs to be improved upon as it relates to leveraging technology or automation to make processes be smoother, better or faster, integrating
- [19:33]
Yan Magnan
further various pieces of technology. The alternative investment fund industry comes from a world where technology teams were looking at point solutions. But at the end of the day, when you take a step back and you look into how these firms operate, everything boils down to portfolio company data. That's the material from where everything is basically derived. Whether it's thinking about value creation, whether it's about thinking about an exit, whether it's about the valuation process, the reporting process to the LPs, all of that sits on this stream of data. We are talking about, of course, financial data, but also operational data, captable type of data. All of that is our data set that are basically the DNA and the materials that these GPS operate on. What's missing is a set of technology that basically covers everything.
- [20:27]
Michael (Podcast Interviewer)
So my mind goes to two places when I hear you talk about that. One is how does technology harmonize these processes? But two, and I think related is the portfolio company level data Is the kind of single source of truth different investment firms, whether it's equity or credit, may have different valuation methodologies. Does the industry eventually move to a standardized methodology for valuing where you don't get two assets that two firms may value at slightly different prices or values?
- [21:02]
Yan Magnan
For some reason, I don't think that will ever happen. If you look at the public markets, take 10 different brokers, financial analysts, they will come up with 10 different valuations. Anyway, a lot in valuation is about human judgment. It's not just about methodologies, it's about human judgment. And you would have a different perspective on a certain asset than I would have. It's as simple as that. The key question is how do you inform this human judgment as fast as possible? How do you document, justify this human judgment as best as you can? But at the end of the day there will always be nuances. Valuation methodologies are not that different. What differs is the way they are applied from one GP to the other one. And again, that boils down to human judgment and the way they're thinking about things. Can there be some convergence at some point in time? I think yes, definitely. I think another thing that is happening already and has to happen anyway is consistency over time. Especially when it comes to post investment reporting and valuation. You're valuing the same asset over and over again. Quarterly, monthly, weekly, daily. You can't operate in a world that from 1/4 to the next one or to the next to next one, you change methodology unless you can explain and justify that. So creating that level of consistency from one period to the other one is also going to be very important, especially from a regulator standpoint.
- [22:21]
Michael (Podcast Interviewer)
Where do you think the human in the loop will still matter? You mentioned, and I asked this question in the context of human judgment will still be a big part of the valuation process. Where will the human in the loop still matter? And where will things like AI either eat into or augment that human in the loop process?
- [22:43]
Yan Magnan
Think of valuation as basically a combination of art and science. And if you think at it like this, so science basically being everything that's calculation and workflows, how do you get from point A, I'm receiving portfolio company data, to point Z, I'm reporting to my LPs. So these are the processes. All that is the science piece. And the art is what I call the management. Basically I'm valuing a company. I have a set of peer samples. The average EBDM multiple from that peer sample is anywhere from 12 to 14. Am I going to pick 13? Because it's the average. Or do I think that for any reason the company I'm valuing is closer to the top of the range or to the lower range? All of that is your management. It sounds like very simple, but at the end of the day is how do you position a company vis a vis another? There's so many factors that you could look at to do that that at the end of the day, it requires a bit of judgment. It requires a lot of judgment and feel. So that's what the art piece is about. Technology will take care of everything. That's the science piece. And human will be in charge of the art piece. And I'm saying in charge of the art piece, which means that that's where AI generated in particular can also inform the user. The human that is supposed to make the human judgment on certain elements and factors that will help him or her form his or her judgment faster.
- [24:04]
Michael (Podcast Interviewer)
Is there a best way to be able to value a business or a company? You talk about the human element of judgment as it relates to valuing companies or assets. Is there a decidedly best way?
- [24:23]
Yan Magnan
Short answer is I don't think so. One thing that is best is consistency from my perspective, but outside that, when I was a junior guy, I remember valuing certain businesses on some very weird multiples. But just because it made sense, the way I was looking at the business was totally grounded into the business model of the firm and then how the company was positioned on their market. And then from there you can come up with some pretty interesting ways, not that common, to derive a value from comparables.
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Michael (Podcast Interviewer)
On that point, education is so critical, particularly as it relates to the wealth channel investing in private markets. How do you think that the wealth channel gets educated about valuations? Because to your point, value in a NAV in a fund may be driven by the way in which certain GPs value those assets. How do investors in that, let's call it an evergreen fund, how do they understand how and why the GP got to that value and therefore that NAV in the fund?
- [25:31]
Yan Magnan
I don't know if the wealth channel has to be educated in terms of valuation and valuation processes. What they have to be informed about is how the GP actually operates their valuation processes, whether they have valuation policies in place, how do they deliver valuation against these valuation policies? Are they basically consistent and also do some kind of backtesting? So basically I received the valuation last quarter. What's happening next quarter? If there is an exit, how far was the previous valuation to the exit? So this type of information, so basically it's more like a backtesting for me that will enable the GP to understand what's the valuation mindset of a certain gp. But I don't think you need to be educated in valuation to be able
- [26:15]
Michael (Podcast Interviewer)
to do that on that point about understanding and being informed about how GPS value assets at 73 strings. You work with many of the industry's largest GPs, including the industry's largest GP is also an investor, Blackstone being one. But you work with many of the largest GPS in the world. What do you see across the different customers that you have as to how they think about valuations and how much uniformity is there across their processes, methodologies, what they're using 73 strings for?
- [26:46]
Yan Magnan
Definitely we're seeing more and more consistency across firm first over time and second across portfolio. And here's the thing with valuation, again, it's a reporting topic and that's a very important one as well. That's one that if you mess it up potentially you can be in trouble with your LPs. So being able to consistently demonstrate that you have valuation policies that you have abided to consistently and that you have been delivering, developing these valuations in a very, very consistent way with full traceability, auditability, the original source information is something that's becoming critical to our clients.
- [27:27]
Michael (Podcast Interviewer)
How are many of these GPs thinking about augmenting technology or AI in the processes as they conduct valuations and monitor their portfolios?
- [27:39]
Yan Magnan
So the answer to that question will depend a lot on where you go in the world. I would say the US is definitely very advanced and we are seeing a large chunk of the market moving out of Excel towards any type of solution to make sure that again, the daily deliver valuation faster, better, more consistently. Other parts of the world might be a bit slower to embrace technology, although we've just opened an office in Singapore a few weeks back and I can tell you via the demand, there is just massive Singapore and APAC actually in terms of being able again to look at valuations in a different way. The market in the UK is moving really, really fast as well and we're seeing exactly the same and very similar type of approach and mindset as what we're seeing in the us. Maybe continental Europe is a bit slower on that respect. Not everybody, but still a bit more old school type of processes.
- [28:30]
Michael (Podcast Interviewer)
What will it take for gps to adopt technology in their processes? And does it benefit the larger GPS or the smaller gps, one or the other more or less? Or does it benefit all GPS uniformly? They just might use it for different reasons.
- [28:46]
Yan Magnan
I Think my point of view is very, that it benefits all GPs in the same way. And here's the thing, I mean, it's a pretty competitive fundraising environment out there. And what we are seeing from our clients is that first, they want to be able to scale, they want to be able to create efficiencies, they want to be able to deliver this valuation faster and better. And the other way around, of course, the first thing that matters when you are raising capital is your performance. But the other way around, you don't want processes that are, are not at par with the best practices out there to be a drag on your fundraising process. So that's what we're seeing happening these days.
- [29:24]
Michael (Podcast Interviewer)
You see a lot of firms and you work with a lot of different firms are GPs spending more and more resources and effort on their operations team, their finance team that relate to valuations, monitoring things of that nature. Because not only is it an important function to deliver to their investors and as you just mentioned, attract new investors and attract the confidence and trust of those new investors, but there's also a ton of data that can be really valuable. And I imagine in today's world, especially with AI, there's tons of valuable data to glean from their portfolios if they're using it properly. Are you starting to see more and more gps pay more and more attention to what they can do with all the data they have and then apply more resources against that opportunity set?
- [30:17]
Yan Magnan
Yeah, we've seen that happen, I would say, in the past one to two years and it's accelerated, like massively. So now on our side, we started by developing these two valuation platforms that was referring to equity instruments, private equity, venture capital growth, equity infrastructure and private credit. And at some point in time in our journey, we decided that we needed a way to ingest portfolio company data into the platform in the easiest way possible. So we developed a AI based extraction technology that operates at close to not 100%, it's not possible, but way north of 95% accuracy. And again, the play on our side and what we wanted to do is facilitate the ingestion of portfolio company data into a platform. Fast forward three years later, what we are seeing is that this extraction technology is used to feed into our valuation platform, but is more and more used as well by our clients to basically collect each and every data point that they receive from their portfolio companies in word decks, in Excel templates, quarterly reports, compliance certificates, everything that they can. Because the starting point of the thought process today is that you can create massive intelligence and Insights. When you're a GP from the portfolio company data that you're getting and the time series of this data as well, that's very, very important. It's not static data. You can create massive insights and intelligence, especially if you can leverage Genai and LLMs on top of that. But here is the thing is that if you don't get the data in the right spot, meaning structured, consistently, standardized, consistently labeled across the board, then you're missing a lot of these insights. If you have one company that reports revenue in your portfolio company as reven, another one that reports revenue as net sales, you can't do much with that. Even the best LLM is just going to garbage in, garbage out. If you get everything consistent, structured, consistently labeled, that's when you can get massive intelligence out of the portfolio company data.
- [32:22]
Michael (Podcast Interviewer)
How long will it take for GPS to have that level of standardization and uniformity and labeling of their data?
- [32:30]
Yan Magnan
It takes to create a consistent data model in the background, which is what we did on our side because we had to feed into our valuation models. It's all about defining what is the data model that you want to operate in and create that extraction technology and that transformation technology that will take the data that you get, transform that into your own data model so that you have something that is consistently structured on that point.
- [32:53]
Michael (Podcast Interviewer)
How much can data be a moat for these firms?
- [32:57]
Yan Magnan
I don't know if I would call that a moat, but definitely it's a DNA and DNA is very critical for anyone, any firm out there. So, yeah, it's definitely something that you should be able to do a lot with again, if you have that in the right place.
- [33:14]
Michael (Podcast Interviewer)
What do you think the next step is for GPS to take the data they have and enrich it with insights, analytics. Do you see things like they're able to find an inflection point in a business faster and then lean in and put more capital into a business? Are they able to benchmark their companies relative to their other portfolio companies and share that with all their portfolio companies so they can see where they stand and what they need to do and what best practices or best in class looks like? Are you seeing a lot of those types of things happen?
- [33:47]
Yan Magnan
Yes, I would say that it's still early days. We are still in the very early days. But I would say that things are moving really, really fast as well. The other thing that I would say is that if you're a GP that manages these hundreds of portfolio companies, the intelligence that you'll get out of this hundred of portfolio companies is going to be much bigger than if you're a GP even managing billions. But that has only 20, 25 portfolio companies because at the end of the day it's a lot about the stats and being able to correlate things. So it's just like it's a question
- [34:20]
Michael (Podcast Interviewer)
of big numbers that would portend to from an investment perspective. And not to say that the low mid market or smaller funds don't have a reason to exist. They absolutely do have a reason to exist, particularly if they're specialists in their category. But scale really matters here. The more scale you have, the more data you have. And if you use that data properly, there's probably a lot you can do with it.
- [34:42]
Yan Magnan
100%. That being said, I would certainly not discard smaller managers as well. As you know fairly well, a lot of these smaller managers, they might not have as much data, but they have certain human expertise. They've done the same deals multiple times and that has also massive value. So combining both is really great on that point too.
- [35:05]
Michael (Podcast Interviewer)
And this gets to the operational side, is there's probably a lot of leverage that small firms can gain from leveraging technology both post investment like a 73 strings or otherwise to help them in their processes stay small and nimble, but leverage this technology to help them make their decisions or inform existing portfolio companies lean into investments, whatever it may be.
- [35:29]
Yan Magnan
Yeah, I mean they can definitely leverage a technology on multiple fronts. You can also imagine that maybe a few quarters, a few months, a few years down the road, you'll be able to enrich your own data set with other type of data set assets that will enable you to again create that intelligence or that extra layer of analysis on your own portfolio that will enable you to manage the portfolio better. So that's going to happen as well. If you are smaller, you should not be discouraged because you are a smaller firm, not use technology. It's just like it has a different value.
- [36:04]
Michael (Podcast Interviewer)
I think that's a great segue to the impact of AI because it may benefit both small funds and large funds. What would you say the impact of AI on both of those categories, smaller funds and larger funds will be?
- [36:21]
Yan Magnan
I think it will be massive. I think it will be massive in terms of the ability to operate, the ability to do things faster or better, the ability to extract again insights and intelligence out of all this type of information? Yeah, I think it would be massive.
- [36:44]
Michael (Podcast Interviewer)
The other interesting thing, and my mind goes back to when you said 73 strings started in 2020. That was quite an interesting time to start because you started before AI really took off, right? It kind of hit consumer adoption and really in earnest in 23. Claude Cowork and Opus 4.6 came out end of 25. And then you've seen a real step function change in some of the things that, that AI is able to do. And it feels like it's now on this somewhat exponential growth curve, not without its issues, but getting much, much better, much, much faster. What was it like starting when there were some green shoots of AI and you knew AI probably existed, but it was still very early days versus today, AI is probably integrated and embedded in so many processes and workflows where you have to think about it as you build the business. What was it like then and what is it like today?
- [37:40]
Yan Magnan
It's very different. No doubt. 70 at 73 strings. We, we actually have been using AI since day one, mid-2020, since we started the business. But AI at that point in time, as you rightly pointed out, was a different type of AI. We're using machine learning and, and natural language processing still algos. So what we've seen is that these algos have improved dramatically in the past few years and they will continue to improve dramatically. So it's a question of continuing to embed this technology and basically continuing to add efficiencies into these platforms that you can basically push to your clients.
- [38:21]
Michael (Podcast Interviewer)
Where do you think AI will have the biggest impact on valuation? Particularly as you think about things like the agentification of certain industries and workflows, things like cowork, et cetera, etc.
- [38:32]
Yan Magnan
Moving faster across the evaluation process and also creating some kind of valuation intelligence. I'm very much certain that it's not going to happen anytime soon, that an agent is fully going to be replacing a human to perform evaluation. Because the short story is that you will always need a regulator to be comfortable with the process. You will always need an auditor to be comfortable with the process. You will need the owners of the 401k to be comfortable with a process. So you need to have someone that you can basically turn to and ask, okay, how did you do this and how did you do that? Which at this point in time, as you know, AI is probabilistic. So AI does not know how things are being done. So that is not going to happen anytime soon. But the other way around, can agents accelerate the process dramatically? Yes, agents can work when you're sleeping, as simple as that. So you can, you can imagine that tomorrow you get into the office and most of the rollover of your portfolio has been done overnight and then you have to check what really matters. So all of that is going to massively accelerate the process, which means that the valuations are going to be churned faster with the same, if not higher level of quality and that's going to inform again LPs and retain investors faster and better.
- [39:57]
Michael (Podcast Interviewer)
Though, is that the type of thing where it's going to just naturally mean that valuations are going to occur much more frequently? Because with AI it can.
- [40:08]
Yan Magnan
Yeah, I mean, definitely, I think so. That being said, we need to define exactly valuation. I mean valuation requires when you perform valuation from A to Z on the portfolio company, you need two things. You need the most recent set set of information from your portfolio company and then you need information on transactions for similar businesses, public companies that are similar. You need to be able to calculate discount rate. All of that you can basically deliver on a daily basis. Portfolio company data is not going to be delivered on a daily basis. So what you will be able to do is basically refresh everything that's marketing and then take a call, take a judgment on where you think the underlying KPIs of the portfolio company could be at any given point in time.
- [40:58]
Michael (Podcast Interviewer)
You think eventually AI will get smart enough or better than humans at doing that?
- [41:03]
Yan Magnan
Yes, I think it's probably already happening. But again, in the world I live in, the question is who do you turn to when you have a question and if AI can't answer how they come up with a certain result world defeats the purpose. What I do is a very, very different set of value proposition as compared to what an hedge fund could be doing, for example, where they try to beat the market. We are doing something different. We're trying to inform the market in a governed environment, auditable and traceable. So from that perspective, I would caution
- [41:42]
Michael (Podcast Interviewer)
things if we zoom out and think about just the evolution in private markets infrastructure from pre to post investment, things have evolved pretty quickly. What do you think is the next big thing as it relates to this evolution in market structure and what needs to happen from a post trade perspective to continue to improve the private market's processes and experience for both GPS and LP Piece?
- [42:09]
Yan Magnan
I think, I think that piece is a lot about data sharing data between one piece and one part and another one. And you know, the way I'm looking into things, we are working with GPS and we have clients that are also LPs we are sovereign wealth on, so they're on both sides of the equation. And I mean I don't come from a technology background, but I'VE always been surprised that you have, you know, data and processes in a certain G2 format on one side of the equation and then suddenly everything is put in a PDF so that it goes to the other side of the equation. Why is that happening? I think at some point in time anyway, as we move towards more transparency for everything that we discussed already in this conversation, at some point in time there should be a way that data, some data is shared between the GP and the LP in a more digital format so that LPs can also make their decision faster and better. And so I think that's one of the piece of the equation that's missing it there.
- [43:12]
Michael (Podcast Interviewer)
What are you most excited about as it relates to the next iteration of market structure? Evolution in private markets?
- [43:20]
Yan Magnan
Interconnection?
- [43:21]
Michael (Podcast Interviewer)
Who does that? What's the right type of firm to do that?
- [43:25]
Yan Magnan
It's about trust. Gps have to trust that their partner is going to be able to deliver and it's about trust that the data goes in the right place at the right point in time. So, yeah, let's see.
- [43:42]
Michael (Podcast Interviewer)
I think that means that smile means there's more to come. There's a lot going on. This has been a fascinating conversation. I think so much insight into both the human and the technology experience that relates to valuations. What's happening today is a fascinating conversation. Thanks so much. Much in.
- [43:59]
Yan Magnan
Thank you.
- [44:00]
Podcast Narrator/Producer
Thanks for listening to this episode of Alt Goes Mainstream. I hope you enjoyed it. You can read more about Alts at my substack altgoes Mainstream substack. Com. Thanks a lot and have a great day.
- [44:11]
Podcast Host (Intro/Outro Voice)
We're going mainstream.