Alt Goes Mainstream: The Latest on Alternative Investments, WealthTech, & Private Markets
00:04:01 · Yann Magnan
[00:04:01] S1: Well, thank you. Thank you for that. Thank you for this introduction. Yes, I got into seventy three Strings, which is a technology SaaS business focusing on valuation for alternative investment funds, basically because I come from the valuation industry. I spent twenty five years first at second at one of The US constituency at the point in time called Duff and Phelps, now known by the name of Kroll. And the core of what I was doing was corporate finance and more specifically valuation of non listed assets. So I got into that business, valuing assets for clients and getting to realize pretty fast that a lot I was doing as a consultant, lot I was asking my consultants to do for me, and a lot that I was seeing being done at my clients, everything was manual, manual as in Excel, Google search and email. And I thought that's very inefficient, number one. Number two, that's a bit of waste of the time. These consultants that we hire from the best universities, best engineering school, it's really a waste of their intellectual capabilities, they spend all this amount of time collecting data, going through data, putting that into a model, checking that it's all correct and checking again because I'm a bit of a paranoid guy. So I like to get things checked quite a few times. I was thinking there must be ways to do things differently. And as I saw the technology evolve and evolve pretty fast. Look, I mean, as you can see, I'm a bit older guy. When I started doing valuation in France or working in in my previous firm, we had this very old Mac laptop and Excel was just like a disaster on on that. Things progressed. And then at some point in time, you think there must be ways to do things differently when it comes to valuation. So how do we make that happen? And, yeah, that's basically one of the genesis of 73. The other genesis is that I met with a group of fantastic cofounders that, you know, we are like minded. So like minded people thinking how to progress, how to make things evolve, how to do things differently, while knowing the industry that we address and the pain points that we address really, really well. And I think that was the key driver behind early success, but quite good success of seventy three Strings.
00:06:11 · Michael Sidgmore
[00:06:11] S0: That's part of the reason why grey hair is good in private markets, because the experience matters, it's important, and understanding how to navigate and work with a lot of big players, work with strategic partners, strategic investors, all of which you have. What were some of the things that you saw while being in the valuation services business that you said this needs to be automated and it can be automated. You're asking yourself the question, can this be automated? And then you figured out how to put structure around that process.
00:06:41 · Yann Magnan
[00:06:41] S1: So the first thing that really has struck my mind back probably like already twenty years ago is that I was a more junior valuation guy. I was tasked to work on the M and A assignment. We had to do evaluation of a business and to do that, we had to develop private business and we had to develop benchmarks to to public companies. I don't remember what the business was, to be honest with you, but I remember private business, we had a peer sample of private companies and it was like five, 6PM at night and we had to speak to the client the next day with some ideas and so on. And so I turned to my junior, I tell him, okay, can you assemble real quick benchmarks of these peer companies, revenue growth and EBITDA margin and various financial ratios and so on, and collect that information from brokers reports and so on. And the guy then, yeah, but it's going to take three days. I mean, come on, why? Why is that? I mean, you have to go through all this paperwork, all these amount of documents and find for relevant data and then plunge this data into a model and then cross check that everything is correct. Yeah. It's going to take two to three days. And I thought, mean, that's nonsense. How can that happen? Of course, that was some time ago when all the data sources like Cap IQ and FactSet and Affinity came to market with a way of looking at that data in an automated way. But still I've been thinking there should be a way for people that have to value these non listed assets that have to take a look as to how they compare to other type of companies to pull in the information in a much faster way, to pull in the intelligence in a much faster way, to go through the vast amount of data and documents that you have to go through to collect and pick this relevant information in a much faster way. And that's where we started thinking with your colleagues. I mean, AI should probably be helpful there, actually. And... Yeah. So that's one of the starting point.
00:08:32 · Michael Sidgmore
[00:08:32] S0: One question that comes up from that is, how much is the lack of uniformity a real challenge? There's lack of uniformity and standardization around how funds may value companies' assets and their valuations, how they look at their revenues, their valuation multiples, their methodologies. There's so much difference in the way that firms may apply their own valuation methodologies. Can you standardize and create uniformity within the valuation process? Or is it automation will get you part of the way there, and then there will still be a large manual component to this?
00:09:07 · Yann Magnan, Michael Sidgmore
[00:09:07] S1: My view is that you cannot automatize that work partially, but only partially. A significant component of any valuation process is actually the human judgment that goes into it. And you would have a different view on certain parts of a business that I would have. It is very important that we have these different views. The valuation process is more like a language that helps you articulate a view on the business and, in the end, form a view on the value of this business. But your human judgment is going to be very important. My human judgment is going to be very important. I don't think that we should automate that part of a process. Automating the calculation, I mean, that's, of course, that's the simple things that you have to do. Automating how you get or facilitating, I would say, other than automating, facilitating how you get to a faster human judgment, how you get faster of information that will help you form a view as to how this business is really comparable to that other one, which by the way, that does not exist. There's not one business that fully compares to another one. So how do you understand the nuances faster so that you can come up faster with the adjustments that you need to make in your valuation processes and in your valuation analysis so that in the end you come up with the proper construct of this solution. [00:10:24] S0: Do you think AI will eventually be smart enough where it will actually do a better job of the qualitative side of what you just described, the human judgment around valuation?
00:10:24 · Michael Sidgmore, Yann Magnan
[00:10:24] S0: Do you think AI will eventually be smart enough where it will actually do a better job of the qualitative side of what you just described, the human judgment around valuation? [00:10:34] S1: Possibly. But I will not bet on that. And I think we are years away from that happening if it happens. The work we are doing at seventy three Strings facilitating the valuation for the owners of the non listed assets. Ultimately, objective of this work, the objective for clients is to report their valuation to their LPs, to their investors. [00:10:58] S0: And do it faster.