Alt Goes Mainstream: The Latest on Alternative Investments, WealthTech, & Private Markets
00:07:36 · Venkat Subramaniam, Michael Sidgmore
[00:07:36] S2: the biggest difference for people like us to come and solve this is cloud computing. Cloud has really made a huge difference. You can launch products a lot more easily and a lot quickly. And I think there's a realization that processes are very important. And if you want humans to work with technology, the UI UX needs to be very, very clean and very user friendly. If you look at the legacy software systems, they were not really built for purpose. Some of the front technology and the way people are designing things, enterprise applications are becoming more like your Netflix of the world and so on. It's very, very important. And once that happens, data becomes cleaner that's coming in, and then AI can obviously play its role if the data is there. I think cloud computing and the way people think about designing software. [00:08:24] S1: That's a really important point, the consumerization of enterprise software. Because people as consumers are so used to using certain technologies, and they expect, I think they demand more of Yeah. The way in which their user experience is. On that point, I actually had Griff Norville, who's the head of technology at Hamilton Lane. He said that private markets needs to move from the stone age or the Excel age to the the digital age. What do you make of that? Like, do you feel that, especially for back office functions like cap table management, deal structuring, do you think ex... The Excel will still be the core of what they do, or are there now better solutions?
00:09:03 · Venkat Subramaniam
[00:09:03] S2: I think Excel is a great tool. I worked with Excel for many, many years, and I still love Excel. And I I think Excel will always have a use case. Excel is great if you're modeling scenarios, especially scenario analysis. If you have a lot of data and you wanna play around with it and see what it means, Excel is a great tool. What it's not good with is if you're trying to track events, you're trying to manage workflows. And when Excel is being used for that, that is where it sort of falters, and that's where I think technology has got a huge role to play. Captable is a very good example because you've got two things happening there. You've got a ownership position at a point in time, and then you've got all the events that are happening to get to that ownership position. I think if you're trying to use Excel to manage the latter, it will be a big issue. But that's where all the problems you see come in. But if you need that data to flow into Excel to to then model your waterfalls and valuations, that is a great use case for Excel. So I think software will help Excel become more powerful and and vice versa.
00:10:04 · Michael Sidgmore
[00:10:04] S1: Something that's really interesting that you're getting at, and where my mind goes when you're talking about that, is that what you're talking about might be a back office function, but it actually connects to the front office. The investment team has to be able to understand waterfall scenarios and modeling pre investment. Yeah. But then obviously, it matters post investment. It matters with investor communications, touches the IR team. All of this kind of flows together and is interconnected. What do you make of that, and how how do you think about, yes, you might be a back office innovation, and the teams that are using this are the finance, the operation teams, but when should people be leveraging technology? Should it come before they do? Deals, obviously, private equity firms are growing concerns. They're already using solutions, they now have to fit something in. But how do you think about this interplay between maybe a back office solution, how it impacts the front office or investor relations?
00:10:54 · Venkat Subramaniam
[00:10:54] S2: So when we were working on this problem, we kind of did a pain statement. So it's a really messy chart with lots of yellow sticky papers connecting everything. And when you really drill into it, you realize if you take cap table as an example, you realize that people are actually asking for cap table data without actually saying what they want as a cap table. And it's across the piece, front office, back office. And I'll give you a few examples. So let's say you have a portfolio company and they are one of the subsidiary entities opening a bank comes over, and the banks want to do a KYC analysis. They may say we want a structure chart. We wanna see everything all the way up to the fund. That is a cap table deliverable. You can't do a structure chart and show ownerships without cap table. That's a very indirect way of asking for cap table information. The same applies to deal teams. They may be thinking, I want to value this instrument or this return or your valuation teams every quarter. They might be thinking, I want to value the equity position that a fund holds across all the investments. What they're effectively asking for is cap table data because you can't do that without accurate cap tables. Exits, your tax advisers come in. They want to look at the entire exit process and the diligence risks. They may be asking for lots of information that is indirectly connected to the cap table. So it goes across all areas, front office, back office, middle. And this problem is occurring all the time on a daily basis, quarterly basis, yearly basis. And... But then teams are working in silos, so they don't realize it's all connected to that source data. We didn't realize it, to be honest, until it was a long time in. Then, you know, penny drop moment, and then you go, well, this is it. You connect all the dots, and I think everything is connected, including investor reporting, ultimately your relationships with the LPs. But the problems are myriad and vast. We're focused on one right now.
00:12:43 · Michael Sidgmore
[00:12:43] S1: Unpack why you're focused on that specific problem. Is it because the cap table data, that underlying asset level data is the core and kernel of everything, where everything else kind of revolves around that?
00:12:57 · Venkat Subramaniam
[00:12:57] S2: We like to call it the messy middle. There's a lot of tech in private markets, as you know, investor relationships, fund accounting, portfolio monitoring, and lots of new tech coming, which is very exciting. But there is this messy middle between the fund and the portfolio companies. There's complexity in this dataset because these things are highly structured. There is lots of moving parts during the whole period, and there's volume because a fund will have many investments, each of which will have its own unique. What we thought was identify a pain point, but a pain point that is recurring. I don't think just having a pain will validate the need for a product. Because if you're trying to solve for exit efficiencies, that maybe happens once every four or five years. And proactive funds are very good at throwing people at... And lots of resource at it. But if you have a pain that is more recurring, let's say annual audits, that's once every year. But even better, quarterly evaluations and reporting, that's once every quarter. Now the funny thing is it's all connected. So if you have a recurring pain like quarterly evaluations and you build a cap table solution that's solving it, your annual audits are going to become very easy. And if your annual audits are clean and easy, your exits are going to become clean and easy. So we kind of zeroed in on cap tables, but specifically from the standpoint of quarterly reporting function. But the way we do it is we have that big vision in play. So you do it properly, then your annual audits become easier. Your exits become easier, and then it all rolls in and connects the dots.