E321: Why Most LPs Have No Idea What’s in Their Portfolio - How I Invest with David Weisburd

Podcast Summary: How I Invest with David Weisburd

Episode 321: Why Most LPs Have No Idea What’s in Their Portfolio
Host: David Swan
Guest: Ryan (Arch Founder)
Date: March 10, 2026

Overview

This episode centers around the critical challenges institutional investors (LPs) face in tracking, understanding, and optimizing their exposure to private market investments. David Swan interviews Ryan, founder of Arch, a platform that automates and standardizes alternative asset tracking for LPs with over $400 billion in assets managed on their platform. Core topics include the limitations of legacy systems, the nuances and fragmentation of private market data, the adoption of tech and AI for better decision-making, and how current market trends are forcing LPs and managers to rethink their strategies.

Key Discussion Points & Insights

1. State of Private Market Portfolio Tracking and Operations

[00:04] Arch currently supports ~550 clients with $405B assets, acting as an "operating system for private assets" similar to Schwab for public markets.
[00:31] Legacy LP workflows are highly manual, requiring logging into disparate datarooms (Interlinks, Carta, Juniper Square), extracting PDFs, and manually entering data into spreadsheets.
- Quote ([00:31], Ryan): “A lot of LPs are logging manually into all these different data rooms... getting PDFs that they then have to read and put into spreadsheets. We go get all that data... and give them dashboards, analytics and insights on their portfolio.”

2. Benefits and Second-Order Effects for LPs

[01:20] Automation saves significant time and reduces the need to hire analysts solely for administrative tasks.
[01:20] Structured, standardized data empowers LPs to make more informed allocation decisions, track exposures, and optimize their investments.
- Quote ([01:20], Ryan): “It’s really hard to make good decisions if you don’t understand your data and understand the signal within your data..."
[02:07] Better clarity of liquidity needs and unfunded commitments—critical for avoiding over-allocation or missed capital calls.

3. AI and Data Standardization in Private Markets

[02:39] Arch is rolling out AI tools to extract and summarize complex information from documents (e.g., LPAs), making fund terms and exposures transparent.
- Quote ([02:39], Ryan): “We can use AI and a specialized AI model to pull that out automatically and give people a full readout of what should I know about this fund as I’m looking to invest.”
[13:15] Industry’s move toward standardization (e.g., ILPA templates, APIs) is slow and primarily driven by large institutional LPs.
- Quote ([13:15], Ryan): "Funds that are sub-institutional have no incentive to adopt something like an ILPA… we’re kind of meeting the industry where it is today."

4. Scaling Portfolio Complexity and Investment Advisors

[05:17] As LPs’ portfolios grow—from 10 to 50 fund positions—the administrative burden explodes, often requiring teams or outsourcing to advisors and banks.
- Quote ([05:23], Ryan): “They’re getting emails every day, every hour... And then you have to make sure you don’t miss capital calls, that you route all the K1s..."
[06:18] Family offices historically manage manually—Excel, paper tracking, and even physical distribution of documents for processing.

5. Flows, Trends & Market Dynamics

[06:57] Major institutional capital in privates is largely “locked in,” with net new allocations increasingly coming from family offices, RIAs, and the bank channel.
- Quote ([06:57], Ryan): "Most of the major institutional investors, especially endowments, are overexposed to venture specifically and to privates..."
[08:18] Data fragmentation: 50,000 unique investments tracked, 800+ portals, no standardization—top data producer contributes just 7% of Arch’s inbound info.

6. Shifting Asset Classes and Structural Innovation

[14:07] There’s renewed interest from LPs in hedge funds and fund-of-funds, as well as in independent sponsors and more deal-by-deal (rather than “blind pool”) vehicles.
- Quote ([14:53], Ryan): “We’re seeing them deploy more in kind of deal by deal structures and in independent sponsors...there’s an ability to just be really intentional about what you’re actually investing in.”
[15:54] Upcoming IPOs and “Renaissance” expectations: increased liquidity events may re-invigorate redeployment to private markets.

7. Liquidity, Secondaries, and DPI Crisis

[16:51] Traditional models (Yale/Swensen) called for ~24% DPI/liquidity—2024/2025 saw only 9%, straining LPs’ ability to redeploy.
- Quote ([16:51], David Swan): “Models are literally breaking for LPs in terms of their ability to deploy capital, get it back and redeploy into future vintages.”
[17:53] Secondaries market is more active, with discounts narrowing (from ~30% to 15-20% NAV), reflecting pent-up liquidity demand.

8. Private Asset Leverage and Structural Barriers

[18:35] LPs struggle to secure credit lines against private holdings—unlike with public securities or even crypto ETFs. Collateralization remains niche and generally not efficient.
- Quote ([18:58], Ryan): "Historically I’ve seen that the LTVs and the interest rates on loans against private market assets are not competitive... I think that will start to change..."

9. AI-Driven Insights and Surprising Market Realities

[20:52] AI is being used to summarize qualitative fund documents for clients and to programmatically structure quantitative performance data.
[21:47] Ryan is surprised by pervasive data discrepancies in financial reporting—even large custodians and banks often have inconsistent or incorrect data feeds; the source documents are the only reliable reference.
- Quote ([21:47], Ryan): “Most of the data feeds in the market don’t match the documents... 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.”

10. Company Building: Lessons and Hiring

[23:36] Advice to his younger self: grow (and hire) more confidently, earlier.
[24:19] Personnel success derived from a multi-lens, rigorous hiring approach focused on hustle, kindness, client orientation, and continuous improvement.
- Quote ([25:01], Ryan): “We have a lot of different lenses in the hiring process...We kind of have this 1% better every day mentality across the company.”

Notable Quotes & Memorable Moments

"We become kind of like this Schwab like operating system, bringing to private markets what platforms like Schwab and Robinhood brought to public markets.” — Ryan ([00:31])
"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." — Ryan ([04:49])
"It just seemed like it was simple... but I think just understanding all the different nuance... there also is this little known thing where most of the data feeds in the market don’t match the documents." — Ryan ([21:47])
"Models are literally breaking for LPs in terms of their ability to deploy capital, get it back and redeploy into future vintages." — David Swan ([16:51])

Timestamps for Important Segments

00:04 — Scale and scope of Arch’s current platform
01:20 — How automation & data structuring gives LPs an edge
02:39 — Introduction of AI in evaluation of fund documents
06:57 — Shifting LP allocation trends and where new capital is coming from
08:18 — Why private fund reporting is so fractured and difficult
13:15 — Industry movement (and resistance) toward standardization
14:53 — Rise in independent sponsor and deal-by-deal interest from LPs
16:51 — Historic vs. current (much lower) liquidity rates (DPI) for LPs
17:53 — State of secondary markets amid liquidity crunch
18:58 — Structural barriers to lending against private assets
20:52 — AI’s impact on qualitative and quantitative data extraction
21:47 — The unexpected complexity and error-proneness in industry data feeds
23:36 — Lessons learned in company growth and hiring

Conclusion

This episode offers a deep, pragmatic dive into the struggles and solutions for institutional investors managing alternative assets. Ryan highlights the friction and fragmentation plaguing private market data, the necessity of new automated, AI-powered platforms, and how current market constraints are shaping next-generation portfolio construction and liquidity.

The discussion balances tech innovation with real-world operational insights, making this a must-listen for any allocator, family office, or service provider serving LPs in private markets.