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A large public pension fund can pull up exactly what it has paid every credit manager in its portfolio over the last five years, broken out by mandate size. The fund manager sitting across the table from that pension in a fee negotiation usually cannot say the same about their own competitive set. That asymmetry, not goodwill or negotiating skill, is what decides how a lot of fee conversations actually go.
This post covers why that gap exists, how to think about your own fund's fee terms relative to peers, and where the data to close the gap actually lives. In this article, we're breaking down why fee terms vary more than headline numbers suggest, how to build a real peer group for benchmarking your own terms, and where that underlying data actually comes from.
The Information Asymmetry Problem
Institutional allocators have gotten structurally better at seeing what they pay across their own manager rosters. Public pension funds are required to disclose the fees they pay across private equity, private credit, private real estate, infrastructure, and hedge fund commitments, and ILPA's fee reporting template, updated to Version 2.0 in January 2025, is now the expected standard for funds in their investment period as of Q1 2026 (ILPA, January 2025). CalPERS put the rationale plainly: transparency exists to ensure investors are fulfilling their fiduciary duty to their members (Chief Investment Officer, January 2025).
The result is that a large allocator negotiating with a new manager is rarely negotiating blind. They can see, or their consultant can see, what the fund has paid comparable managers before. The manager on the other side of that table typically cannot see the same thing about their own peer set, unless they have gone looking for it specifically.
This isn't really about finding the "lowest" fee in the market. It's about knowing what's realistic and aligned for a fund of a given size, strategy, and stage, so a fee proposal reflects where the market actually sits rather than a guess.
Why Fee Terms Aren't One-Size-Fits-All
Fee structures vary more than headline numbers suggest, and the variation isn't random. Stanford GSB research found that 61% of private market funds cluster investors into two fee tiers, and that managers without an established track record are 13 percentage points more likely to use tiered structures than established managers (Stanford GSB, Begenau and Siriwardane, 2022). An emerging manager benchmarking their terms against a single blended "market average" is comparing themselves to a number that mostly reflects established managers with different leverage in the room.
That's the same reason performance benchmarking has moved toward tightly defined peer groups instead of broad category averages: a fund's true competitive set is narrower than its asset class label suggests, and fee terms are no different. See Why Quartile Rankings Matter in Private Fund Performance Evaluation for how this plays out on the performance side.
How to Actually Benchmark Fee Terms
The discipline here is the same one that applies to benchmarking fund performance: build the peer group first, then read the numbers.
Asset class and strategy. Private equity, private credit, private real estate, infrastructure, and hedge funds each have their own fee conventions. Comparing a private credit fund's terms against a broad "private markets" average tells you very little about where that fund actually sits.
Fund size. A 2% management fee reads differently for a $2 billion flagship fund than it does for a $150 million emerging manager. Fee breaks by ticket size are common as commitments scale, and a benchmark that ignores fund size will misread where a given fee level actually falls.
Manager stage. Given how much tiered fee structures skew toward emerging managers, a first-time fund benchmarking against an established manager's terms is not making an apples-to-apples comparison, even within the same strategy and size range.
Vintage and geography, where relevant. Fee conventions shift gradually over time and can vary by region, so recent, geographically relevant data holds up better than older or blended figures.
A fee comparison built without these filters isn't wrong exactly, it's just not precise enough to act on with confidence in an actual negotiation.
Where This Data Actually Lives
Fee schedules, the periodic disclosures public pension funds publish detailing what they paid each manager, are the underlying source. For more on what a fee schedule actually contains and why funds are required to disclose them, see What Is a Fee Study? How Public Pension Funds Track What They Pay Managers. The challenge has never really been that the data doesn't exist. It's that fee schedules are published by individual funds, on individual websites, in individual formats, on individual schedules. One fund publishes a clean fee table in its CAFR. Another buries the same information across pages of narrative. A third reports figures net of expenses rather than gross, making its apparent cost look lower than a peer with no actual difference in what either fund paid.
Aggregating and normalizing that data at scale is what turns scattered disclosure into something usable — see The Top 10 Benefits of a Public Pension Fund Fee Schedule Database for more on what that unlocks. Dakota Marketplace's Fee Schedules module tracks manager-level fee data across more than 13,900 fee schedules and 1,400+ U.S. public pension funds, organized by investment strategy, asset class, and sub-asset class rather than left as unstructured filings. Fee data sits alongside each pension's other documents, including manager presentations and daily-updated meeting minutes, so a fee figure can be read in context rather than in isolation.
What This Means Going In
Knowing where your fund's terms sit relative to a real, precisely defined peer group is groundwork to do before a negotiation starts, not during it. The managers who walk in with that context are negotiating from a position closer to parity with the allocators on the other side of the table, instead of relying on a general sense of "what people are charging these days."
This is exactly what Joe, powered by Dakota, is built for. Joe organizes fee schedule data from public pension disclosures into a structured, searchable format instead of leaving it scattered across individual filings, so a fund manager can filter to their actual peer group by asset class, sub-asset class, and investment strategy in minutes rather than piecing figures together by hand. The same platform that tracks Net IRR, TVPI, DPI, and RVPI for performance benchmarking applies the same discipline to fee terms: a real peer group, not a broad category average, and named, current data instead of a dated market impression.
See what comparable managers in your specific peer group have actually been paid to charge. Dakota Marketplace tracks fee schedule data across 13,900+ documents and 1,400+ U.S. public pension funds, filterable by asset class, sub-asset class, and investment strategy.
To explore benchmarking, request access to Joe.
