Investing Billions - E321: Why Most LPs Have No Idea What’s in Their Portfolio

Episode Date: March 10, 2026

Why are private markets still managed in spreadsheets when hundreds of billions of dollars are at stake? In this episode, I sit down with Ryan Eisenman, Co-Founder and CEO of Arch, a platform suppor...ting more than 550 clients and over $405 billion in alternative assets. Arch is building an operating system for private markets that helps investors manage the operational complexity of alternatives across private equity, venture, hedge funds, credit, and more, bringing modern infrastructure to a part of the financial system that has historically relied on manual processes and fragmented data.

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Starting point is 00:00:00 So for context, give me a sense for how big Arch is today. Today we support about 550 clients. Our clients have $405 billion in assets on the platform. We're a solution for tracking, managing, and automating all the paperwork around alternative investments. So the assets we serve are stakes in private equity, hedge funds, venture, credit fund, some crypto, anything that's not a stock or bond. So you support $405 billion in assets. Tell me about what that looks like. Without Arch and Prearch, a lot of LPs are logging manually into all these different data
Starting point is 00:00:36 rooms. They're going into Interlinks, Karta, Juniper Square, platforms that are not necessarily built for LPs to understand their investments and they're getting PDFs that they then have to read and put into spreadsheets. We go get all that data and that information on the LPs behalf. Our clients are global banks, RAs, about 200 single family offices, institutional allocators. And they use us to get all the information. from these different funds and their fund platforms, structure it, standardize it,
Starting point is 00:01:05 and then give them dashboards, analytics, and insights on their portfolio. So we become kind of like the Schwab-like operating system bringing to private markets what platforms like Schwab and Robin had brought to public markets. How does that practically help LPs? One, it saves them a lot of time. So instead of having to hire analysts who spend a lot of their day going into portals and platforms, they can now have that process automated for them. The second thing is it's really hard to make good decisions if you don't understand your data and understand the signal within your data.
Starting point is 00:01:38 And so it could be things like, has this manager performed or how much unfunded commitments do I have across these investments or these entities down to how much basics do I have in my portfolio and how much drive do I have? And am I a net buyer or a seller at this price? So we give our clients an unfair advantage as they look at the market. by helping them understand their existing data and then also power some of their future facing decisions. What are some second order effects of that? It's hard for people to make allocations to new funds.
Starting point is 00:02:09 They don't know how much they owe to pass funds. So a lot of folks don't have good understanding of the liquidity needs in their portfolio. And do they have $1 million or $5 million or $10 million of net commitments that are going to be called in the next one, three, five years? So that's one important consideration. The second is being able to understand the performance of the funds that you're in when you're looking to re-up within those managers. And they're also introducing AI tools around evaluating new opportunities. So when a manager sends you their docs, it's 100-page limited partner agreements that have deeply buried on page 69, the terms and the carry and how expenses are treated within the fund.
Starting point is 00:02:49 We can use AI and a specialized AI model to pull that automatically and give people a full readout of, what should I know about this fund as I'm looking to invest? And so those are some of the newer tools that were developing around driving better decisions through data. One of the hardest things of investing is seeing what's shifting before everyone else does. For decades, only the largest hedge funds could afford extensive channel research programs to spot inflection points before earnings and to stay ahead of consensus. Meanwhile, smaller funds have been forced to cobble together ad hoc channel intelligence or rely on stale reports from sell-side shops. But channel checks are no longer a luxury. They're becoming table stakes for the industry.
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Starting point is 00:04:00 or consensus estimates. The best part, these proprietary channel checks integrate directly into Alpha Census research platform trusted by 75% of the world's top hedge funds with access to over 500 million premium sources, from company filings and brokerage research to news, trade journals, and more than 240,000 expert call transcripts. That context turns raw signal into conviction. The first to see wins, the rest follow. Check it out for yourself at alpha-sense.com slash how I invest. I kind of think about this as mental compute. So you could only handle so much abstraction and so much thought in a single day.
Starting point is 00:04:38 And if you're spending that compute on figuring out what's my portfolio, how much compute do you have left over for sourcing new managers, building relationships, fundraising, all those things that LPs need to do. Yeah, exactly. I think we don't value our time well. and we get sucked into a lot of distractions that are not what we actually need to be working on. And so it's not a good allocation of someone's time to spend that time taking numbers off of a document and putting it into a spreadsheet. That time should we spend in thinking about what investments do I need to make?
Starting point is 00:05:09 How do I actually want to allocate capital? If I want to invest in venture capital or private equity, who are the best managers? And how do I get a warm introduction to them so that I can invest in their fund? As an LP goes from 10 to 25 to 50 fund investments, what typically breaks down? They typically at some point need to hire someone. They might already use an investment advisor. This is why about half our business comes through investment advisors and banks today, where they're doing this work on behalf of their clients.
Starting point is 00:05:36 But then those advisors often have high hundreds or thousands or tens of thousands of investments. And then it is just utter chaos. They're getting emails every day, every hour of the day, that need to be responded to. And then you have to make sure you don't miss capital calls, that you route all the K-1s to the accountant that's on each account, that you receive distributions correctly, that you could reconcile that the distributions arrived and the capital calls went out.
Starting point is 00:06:00 And then you're not even thinking about, like, what's in an investment letter or what do I actually need to know about these investments? The tracking becomes a job, and it becomes a job that often is handled by teams once you get into high volume of these investments. What's the legacy solution before our, What were family offices doing? Mostly manual.
Starting point is 00:06:20 So you'll see family offices that have a few analysts. They're managing this information on Excel spreadsheets. Maybe they're using a reporting system, but they're updating that reporting system manually or a GL. And then we've seen family offices that print the capital call and put it on someone's desk and then someone goes through the paper on their desk to pay capital calls. One of the most underreported things in private markets is that most of institutional capital has allocate. They've picked their 15, 25 core managers, and they're continuing to invest with those. Where is the net new capital coming from in terms of from the LPs investing to GPs?
Starting point is 00:06:57 This is a big issue for managers they're starting to raise now or trying to raise. We were speaking at a conference last week and learned in the presentation that from 2022 peaks to today, especially the venture asset class, the venture asset class raised 15% of the capital in 2025 that it raised in 2022. So there's just significantly less LP dollars being committed, especially to venture capital, because most of the major institutional investors, especially endowments, are overexposed to venture specifically and to privates,
Starting point is 00:07:29 so they're not allocating to new venture managers, even if the manager has returned well. Luckily, this is coinciding with a big shift of capital coming from the wealth channel. And so you see family offices that have been investing in privates for a long time, if there's more family offices today, and family offices seem to be increasing their allocation to privates, but especially RAAs, registered investment advisors, multifamily offices, and the bank channel are kind of making up for a lot of that gap because there's significant net due dollars coming from that channel.
Starting point is 00:07:57 Do you see that in the numbers? We see this in the numbers where we'll serve firms. It'll say this wasn't a problem for me three years ago, five years ago because I had a couple hundred alternative investments and most of my clients weren't investing in this asset class, but now people are asking for these investments. and then they now have 1,000 or 3,000 or 5,000 positions that need to be tracked and managed. There's no real Morning Star for private funds.
Starting point is 00:08:21 Why is it so hard to value private funds? Everyone reports differently. Today we collect information from 50,000 unique investments, and they all use a different format, a different portal, do their accounting slightly differently, and all this data is trapped in PDFs. And it's super fragmented. Like the top producer of information,
Starting point is 00:08:41 produces about 7% of the information that we received today. And so we collect from 800 different portals and platforms. There's just a lot of work needed to go first get all the documents and structure the data, then standardize it and understand the accounting treatment of every fund and every fund admin, and then make it useful. So it's a lot of work that we've done over the last eight years to get to this point, but there just isn't a consistent standard around how data is distributed, even something like Nopa only touches a percent of the market.
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Starting point is 00:10:33 Support for today's episode comes from Square, the all-in-one way for business owners to take payments, book appointments, manage staff, and keep everything running in one place. Whether you're selling lattes, cutting hair, running a boutique, or managing a service business, Square helps you run your business without running yourself into the ground. I was actually thinking about this the other day when I stopped by a local cafe here. They use Square and everything just works. Check out is fast, receipts are instant, and sometimes I even get loyalty rewards automatically.
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Starting point is 00:12:50 Do you see that evolving? Yes and no. One of the kind of issues with the OPA adoption is OPA is really only pushed by large institutional LPs. And so funds that are sub-institutional have no incentive to, adopt something like a NOPA. I think you probably will see more APIs become available and more like push for standardization. But this is an industry that moves extremely slowly. So we're kind of in the background working on some efforts around standardization and creating kind of like a standard API that people can push data into and pull data out of. So this can be kind of like the plat of its
Starting point is 00:13:26 category. But we're not waiting for that to happen. So we're kind of meeting the industry where it is today. And you see ground truth data on where LPs are allocating today. Are there new asset classes or new structure where LPs are really deploying capital? We see a lot of just like evolution of what is the hot manager, the hot strategy. So there's their shifts. It does seem like some of the conversations that hedge funds are back and people are interested in more hedge fund investing. We're seeing a lot of fund funds pop up around kind of like hedge fund exposure and being a fund of funds for hedge fund specifically. And so there's always kind of like a little bit of a trend.
Starting point is 00:14:05 And then there's also the like independent sponsor world where we're seeing a lot of dollars go in that direction as well. I want to actually talk about that. So a lot of LPs privately tell me that they're not as interested in blindpool funds. They're interested in investing independent sponsors or co-invest. How much do you see that actually in your data? And are LPs really starting to deploy more into deal by deal vehicles? And this is more of kind of qualitative from the conversation we're having with clients and with LPs. But they are, we're seeing them deploy more in kind of deal by deal structures and in independent sponsors.
Starting point is 00:14:42 And I think it's hard. It kind of goes back to some of the pain points around private markets where if you invest in a drawdown fund and you don't know how over what period your money is going to be called, there's a drag on your returns of needing to do something with that capital. And then in the meantime, if you invest in an independent sponsor, you're typically investing 100% on day one. And we've seen like pretty good results from some of those investments. And I think there's an ability to just be really intentional about what you're actually investing in. And I think there's also like a little bit of a different duration on those assets that sometimes makes it more appealing to the LP. It comes down to not only economics, but also discretion. Also, you don't have to wait for your capital to be called over two to three years.
Starting point is 00:15:23 You get to deploy it. So there's less drag on the investment. Exactly. What excites you most today Q1, 2026 about private markets? I think there's just a huge amount of opportunity. Like where we're standing in Q1 and 26, you're probably going to see some major IPOs later this year. And I think that rush of liquidity back to the market is going to be really exciting for the market. Because people have been missing liquidity and missing DPI over the last couple years.
Starting point is 00:15:51 And so I feel like you'll see a bit of a renaissance when people feel that there is a return from these investments. that they've made and start to see strong return from some of the private asset classes that they've invested in, then you can see a lot more capital be redeployed back into this asset class. And we think that there's just like a lot of opportunity with private markets becoming a little bit more efficient and a little bit easier to interact with to be able to get in and out of positions in the right time horizon that can fit the return profiles and time horizons for different allocators where you might be someone that needs a lower return but needs a little bit more liquidity and are willing to trade that off for someone that wants to stay and invest it for a long
Starting point is 00:16:29 period of time. Just to put some more meat on the bone, historically the Yale, the David Swenson Yale model required roughly 24% liquidity. And that's been the historic liquidity on a DPI basis for many decades. In 2024, it was 9%. Then 2025, it was 9% again. So more than half of DPI versus the traditional model. So models are literally breaking for LPs in terms of their ability to deploy capital, get it back and redeploy into future of vintages. Which makes it really hard. Then if you're a venture firm and you're trying to go raise money from some of these
Starting point is 00:17:05 LPs, if they haven't seen DPI, then they won't be able to reallocate dollars back to managers. So I think the industry is a little bit lopsided right now. You need liquidity to flow back into the market for it to be able to work effectively. Some LPs are pressuring managers, specifically venture managers, to get secondary. Do you see a significant amount of secondary going on in portfolies? We're definitely seeing a lot of secondary managers pop up to meet the needs of, I think, that LP demand. So whether it's an LP-led secondary, where an LP is trying to sell their positions in certain funds,
Starting point is 00:17:42 and have heard that spreads are tightening on that side, So where certain funds might have been sold at a 30% discount or 25% discount. Now maybe it's like a 20 or 15% discount to NAV. So that's one thing. But also like going to early employees and early investors and buying out full stakes. I think there's just so much capital tied up in private markets that I think it's healthy that you have more ability to sell shares when you're three, five, 10 years into an investment. One of the things that's always confused me is if I have single stock exposure in a public company,
Starting point is 00:18:19 I could go to my fidelity and borrow at a pretty low rate. But if I have private exposure, I essentially can't borrow anything against my private exposure. What needs to change for that to become a real institutional instrument in the market? It's a really interesting one. And we were talking to the Bitwise folks about this, a couple of months ago, and they made me aware that if you own, like, Bitcoin, very hard for you. If you own Bitcoin, you custody yourself or you custody with one of the large custodians to get a loan against that Bitcoin.
Starting point is 00:18:54 But you can trade that Bitcoin for Bitcoin ETF, and then the banks will give you a loan against that Bitcoin, and it's actually like more efficient and it allows you to create liquidity off of those holdings. I think you'll see similar things happen in private markets where it's really hard to lend against something that you can't custody or you can't really understand. But several large banks and a lot of different funds are now trying to figure out how do we provide liquidity via a credit type of product to private markets. And so it's something people are looking to solve. Historically, I've seen that the LTVs and the interest rates on loans against private market assets are not competitive with loans against public market assets.
Starting point is 00:19:33 So if you have both, you're going to take your loan against your house or your public market assets. But I think that will start to change as you see concrete data around these assets. assets and how they're being priced and more robust markets around these assets as well. It seems to me that somewhere between zero and 100, some basket of private assets should be able to be bundled together to loan against. But for some reason, institutional investors and or even family office have not figured out how to monetize that. Yeah. And there's definitely some funds that are creating credit-like products where they collateralize large swathes of like a founder's equity and then give them credit or a credit product today, which is like pretty tax
Starting point is 00:20:15 efficient. So they don't have to have a liquidity event or a tax event in order to create a little bit of liquidity on their stake. And to have seen a couple funds that have created really strong businesses around it, but not yet something that's like fully adopted across the full market. I want to double click specifically on the AI. How are you using AI to streamline this process? So we're big customers today of a few foundational models.
Starting point is 00:20:39 There's a few things that. are key here. One is taking more qualitative data. So stuff like financial statements and investor letter, places where there's like interesting insights to glean out of these documents and summarizing it in a client-friendly, consumer-friendly way. So giving you a like, here's the five things you need to know about the latest performance of this venture fund or this real estate manager you're in. Then they're structuring real quantitative data. So pulling out the latest value and unfunded commitment and cash flows out of cash flow statements because then you have structured data that you can use for reporting or to understand what your current balance you looks like.
Starting point is 00:21:20 Having this treasure chest of data at your disposal, what surprised you the most? When we started the company in 2018, we probably thought that like there would be far less nuance than there actually is in this industry. It just seemed like it was simple. It's like, okay, great, we go collect all the K-1s, we organize them, and then an accountant can do someone's taxes without bugging the individual or their wealth manager. We just get all the statements, we digitize them, and then you know exactly what your investments are worth and how they're doing. But I think just understanding all the different nuance of like, okay, some fund admins will tell you that documents are available, but they're actually not available because the system is so overwhelmed with sending the documents that you actually can't receive the documents from that system, but they just don't expect anyone to log in as fast as we're logging in to go get those documents.
Starting point is 00:22:04 So there's a lot of those nuances that we've learned over the last eight years looking like in fund admin by fund admin, custodian by custodian fund to understand the like underlying structure of the data that were being sent. There also is this little known thing where most of the data feeds in the market don't match the documents. So documents are really a source of truth and data feeds are oftentimes wrong. We found this with like some of the biggest banks in the country and we found this with the largest custodians and also data feeds for like public markets as well that the information just. doesn't reconcile, which is crazy when you think about the amount of money that's being kind of described through documents and through data feeds, that the information is not correct. So we're often recreating data feeds when an investment is being custodied via custodian, but the information that's flowing through to the reporting system is not correct.
Starting point is 00:22:54 So we're creating like a higher fidelity level of data. And I would have just expected that if a banker or custodian sends you data, that it should be correct. If you go back, years ago when you were just starting arch, what is one piece of advice you'd give a younger version of yourself that would have either helped you accelerate your career or helped you avoid some mistakes? We probably could have moved a little bit faster and hired a little bit faster at the beginning. We were three co-founders, myself, and two MIT engineers, Jason and Joel, who studied computer science and math and MIT. And then three years later, we'd grown to a mighty team of five and passed our first billion in assets on the platform. And we were just really methodical in
Starting point is 00:23:32 building out the first versions and really understanding our customers and working side by side with our customers to figure out what does the experience need to be. But we probably could have believed in ourselves a little bit more in the early days and invest it a little bit more quickly. But we were very conservative on the first 500K that we raised as a company. What were some of the mistakes you made personnel-wise as you were building your organization? I think we were lucky that we haven't really made that many big mistakes from a personnel perspective. Like, we've been very intentional in a lot of the hiring that we've done.
Starting point is 00:24:07 Like, the fourth person we hired now runs all of operations at Arch and is this amazing force of nature. And she has kind of been an amazing thought partner for the business and kind of pushed us in a lot of ways. And we've been able to find people along the way that have been really strong culture carriers that have pushed the thinking within sales or product or engineering. I had dinner with a chairman of one of the largest banks and he said his higher rate on truly great hires was 50% of his career. You had been hiring for decades. What's your key to success?
Starting point is 00:24:37 How did you get the personnel decisions? So correct. We have a lot of different lenses in the hiring process. So I'm looking for a certain thing. My co-founder Jason is looking for a certain thing. Our operations team is looking for something different. So for key roles, we're able to kind of all look at the candidate via different lenses and make sure that they pass our various tests.
Starting point is 00:24:54 We want people to come in and really want to work hard and hustle. I understand that we are a builder culture, but also a kind culture. So we generally across the entire company, everyone's kind. We don't have folks that don't fit that cultural norm. And folks that really care about customers and are long term oriented. And we kind of have this like one percent better every day mentality across the company. Ryan, this has been absolute masterclass. Thanks so much for jumping on the podcast.
Starting point is 00:25:20 Looking forward to having this conversation live. Likewise. Thanks, David. Great chatting with you. That's it for today's episode of How I Invest. If this conversation gave you new insights or ideas, do me a quick favor. Share with one person your network who'd find a valuable or leave a short review wherever you listen. This helps more investors discover the show and keeps us bringing you these conversations week after week. Thank you for your continued support.

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