The State of Fund Modelling in VC (Preliminary Findings)

Early insights from respondents across GPs, emerging managers and LPs.

If you’ve been following along, you’ll know we’ve been quietly collecting data on one of the most under-discussed but absolutely mission-critical parts of venture capital: fund modelling.

And after processing the first wave of responses, I can confidently say two things:

1. VCs are building funds on shockingly shaky modelling foundations.

2. LPs assume our models are far better than they actually are.

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Table of Contents

1 Why This Matters
2 What This Preliminary Report Is / Isn’t
3 Top Findings (So Far)
4 Who Responded
5 (Paid) Tooling: The Excel Monopoly
6 (Paid) The Real Challenges (In Their Words)
7 (Paid) The Most Difficult Areas
8 (Paid) What VCs Think Is Critical
9 (Paid) Early Patterns
10 (Paid) Insight #1 — The Tooling Maturity Gap
11 (Paid) Insight #2 — The Modelling Literacy Gap
12 (Paid) Insight #3 — The Expectation vs Reality Gap
13 (Paid) Deep Dive: Reserves
14 (Paid) Scenario Analysis
15 (Paid) Assumption Documentation
16 (Paid) Tools & Infrastructure
17 (Paid) Portfolio Construction
18 (Paid) LP Communication & Reporting

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Why This Matters

Everyone talks about strategy.

Everyone talks about sourcing.

Almost nobody talks about the actual model behind the fund — the thing that determines reserves, DPI timelines, pacing, diversification, exit pressure, and LP conviction.

And when nobody talks about it, silent assumptions creep in.

Silent assumptions become blind spots.

Blind spots become fundraising friction… and sometimes, fundraising failure.

That’s why we ran this study.

What This (preliminary) Report Is (and Isn’t)

This is not a polished, final whitepaper. It is the first directional snapshot of how European GPs, emerging managers, and LPs actually build and use fund models - and where the cracks are.

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Top Findings (So Far)

Here are three datapoints that made me sit up:

1️⃣ 96% of respondents still rely on Excel/Google Sheets as their primary modelling tool

(And 73% use nothing but spreadsheets.)

Despite the rise of tools, this industry runs on duct tape and VLOOKUPs.

2️⃣ 69% cite scenario & sensitivity analysis as their hardest modelling area

This is the #1 thing LPs scrutinise.

The mismatch creates friction in fundraising and slows diligence.

3️⃣ Emerging GPs, established GPs, and LPs all struggle with completely different problems

50% struggle with assumptions & inputs. Fees, reserves, pacing, loss curves — the foundation of every model — are misunderstood more often than we’d like to admit.

Emerging GPs worry about basics.

Established GPs worry about complexity.

LPs worry about clarity.

They’re looking at the same model and seeing three entirely different things.

This is creating what I call the fund modelling literacy gap — and it’s widening, not shrinking.

Critical Finding: Emerging GPs, established GPs, and LPs struggle with completely different modelling problems.

We are not speaking the same language.

Who Responded

One thing I’m proud of:

The split between GPs and emerging managers is almost perfectly even - 38% vs 35%.

This gives us a unique lens:

We can compare experienced modelling practice vs first-time fund building in a way most datasets simply can’t.

LPs represent 15% — small but mighty.

Their responses validate (or explode) assumptions that GPs often hold about allocator expectations. This gives us the rare ability to compare what GPs think LPs expect vs what LPs actually expect, and how those diverge from emerging managers building v1 models from scratch.

Quick preview: the gap is bigger than anyone realises.

This is where today’s public section ends

The full preliminary report is available to EUVC Academy members.

Not a member yet? You can join below.

But - good news - there are two other ways to unlock full access:

Contribute your data and you’ll get immediate access to the full preliminary report.

If you want to build and truly understand your model — reserves, pacing, scenarios, portfolio construction, and LP-ready narratives — the cohort is where we break it all down step-by-step.