Alt Goes Mainstream: The Latest on Alternative Investments, WealthTech, & Private Markets
00:10:58 · Michael Sidgmore, Yann Magnan
[00:10:58] S0: And do it faster. [00:10:59] S1: And do it faster. So do it faster, technology can help. The issue when you say you want to report something to a third party, and we're talking about money here, and the real money, and very significant money. The issue is that someone has to be accountable for that. You can't just spit out a number. You have auditors that are at play as well that will look into what things are being done. So can AI come up with a very good estimate of the value of an asset? Yes, probably. I would actually be ready to bet that there's already some very interesting hedge funds that are doing that quite effectively. But here is the thing. Again, the the world I live in, the issue is not just about doing the validation, is providing a certain level of comfort to the LPs that it's done properly and that someone is responsible and accountable for that. So the moment that you put an AI algorithm into it that just spits out a number, you're defeating the purpose. So what I'm saying, will AI get there? Potentially, but the key thing for AI to get there will be to find a way that the other part of the equation, the LPs and their auditors and the regulators as well, will be comfortable that the AI is coming up with the right answer. Because if they are not, who are they going to put the blame on if something goes wrong?
00:12:19 · Michael Sidgmore, Yann Magnan
[00:12:19] S0: I think that brings up a really interesting question related both to 73 strings, but also more broadly around technology being built in private markets. You rely on different stakeholders and technology solutions to be able to do the work that you do at 73. Where do you feel, at least right now as a business, your work starts and stops at 73? And then where do you include and partner with other service providers? [00:12:47] S1: Our work starts with the data or the documents that are sent from the portfolio companies, the borrowers to our clients. That's where we're picking up the work. We're picking up these documents. We have developed a set of technology that can read any type of document, PDF, PowerPoint, Excel, email. What am I missing? Well, probably a board deck, a quarterly report, an annual report, whatever. And it can read [00:13:11] S0: someone's mind. [00:13:11] S1: And and [00:13:12] S0: it can read someone's mind. [00:13:13] S1: Maybe at some point. And collect these documents, identify the relevant KPIs, collect the KPIs, standardize this information, create consistency. And then that information is used for evaluation. So from that perspective, what we need is, well, not much. Eventually, we need a Dropbox from the portfolio company, eventually that could accelerate certain things. But most often, we are seeing that the portfolio companies would send these documents by email to the investment teams, and it would be automatically forwarded to our platform, and it's done.
00:13:13 · Yann Magnan, Michael Sidgmore
[00:13:13] S1: Maybe at some point. And collect these documents, identify the relevant KPIs, collect the KPIs, standardize this information, create consistency. And then that information is used for evaluation. So from that perspective, what we need is, well, not much. Eventually, we need a Dropbox from the portfolio company, eventually that could accelerate certain things. But most often, we are seeing that the portfolio companies would send these documents by email to the investment teams, and it would be automatically forwarded to our platform, and it's done. [00:13:45] S0: Even if different companies report their metrics in different ways, you're still able to handle all that? Because I think that's part of the challenge when you think about different categories, accounting is one example. Yeah. Part of the challenge with something like automation of certain things like accounting or same here where it's valuations is everybody may have a different way of reporting something.
00:14:06 · Yann Magnan
[00:14:06] S1: Yeah. Everybody has a different way of reporting something. And the GPs typically have one way... They want to have one way of looking into each and every information because we want to be able to look through their portfolio, look across their portfolio, and understand when they invest into one specific strategy or one specific sub industry. They want to be able to benchmark companies. They want to be able to understand or to learn from one company and replicate with the other one. But if you want to do that, you need to make sure that the data that you get is very consistent and standardized. Otherwise, you just can't do anything out of that. The beauty of technology is that you can do that automatically now. We have 98.6% accuracy when we do that. It's just like massive. And so it's done automatically. It saves a lot of time. That means that these very smart people that work in these GPs, they don't have to spend like two or three hours at night just collecting these numbers and putting that in the proper standard and proper format. And that's a lot of time saved that they can use to do something else, much more value add. So that's a bit the basic value proposition here. But what we are seeing happening is what I was saying as well is that once all these data is in one place, properly structured, probably standardized, There are so much more that you can do out of that. That's why you can start thinking about AI algorithm that can be like early warning signals, red flags, can you inform the business back with certain information that are not obvious to see if if the information is scattered across multiple multiple folders, multiple Dropbox, multiple Excel spreadsheet. It's just undoable.
00:15:44 · Michael Sidgmore, Yann Magnan
[00:15:44] S0: Does a tool like 73 strings, which is incredibly impactful because of what it's doing to make information much more easily accessible, faster to get, and transparent, does it actually remove the need for certain human processes and even potentially certain service providers, or does the process really stay the same? [00:16:06] S1: The process stays the same, but of course, the moment you're saying that certain tasks are done faster, of course, that definitely removes the need for certain certain amount of time that is spent doing this type of work. Is that a good or bad thing? Well, I guess, of course, it's tough for people that will be impacted. But here's the thing is that the industry is growing so fast and there's such a lack of resource in the industry that anyway, what I'm hearing from my clients is that their key pinpoint is that they want to make sure that they can grow as fast as they can. They want to make sure that they leverage the resources that they have as best as they can. They want to make sure that these resources are not spending 30% of their time doing things that the machine could do, then that they focus on where they really bring value. So from my perspective, it's only going to be helpful to the industry, only going to be helpful to continue to grow the industry and to continue for these resources to continue to grow into their own jobs.
00:17:02 · Michael Sidgmore
[00:17:02] S0: You bring up a really important point, which is the moment in time we are at in this industry, which is, one, the acceleration of focus on the wealth channel and the capital that's coming in from the wealth channel. That dovetails with another big trend, which is the rise of evergreen structures, where reporting happens more frequently. They're open ended or evergreen vehicles. The reporting and valuation become even more important, particularly as you're getting to the individual wealth client. They need more frequent valuations. And then there's also a massive rise in private credit, which the size and scale of those funds are growing, the number of assets that could be in those funds could grow. What do you think about those two trends really accelerating the need for better valuation software post investment to get this data quicker, analyze it better, and create more transparency?