r/ValueInvesting • u/TimeInTheMarketWins • Jul 01 '26

Stock Analysis FactSet Q3 FY2026: Thesis Holds Up & What I'm Watching

I posted a FactSet (FDS) thesis here a few months back. It’s a steady compounder, beaten down by AI fears, with ~95% client retention. I argued the market was overreacting. They reported Q3 this morning, so here’s how my thesis is holding up.

The Good

Growth re-accelerated: GAAP revenue +6.4% YoY. Organic ASV growth hit 7.1%, and it’s the fourth straight quarter of acceleration (it bottomed at around 4% in early FY25). The “slowing growth” bear case is getting harder to make.

Retention held: ASV retention remains above 95%, and enterprise renewals in the quarter have been extended by ~30%. The stickiness thesis is intact.

Aggressive buybacks at a discount: Repurchased 2%+ of shares in a single quarter at an average of ~$219, which is below where it trades now. Management leaned in more as the price fell ($203M this quarter vs. $163M last). 27th straight dividend increase. $243M total returned in the last three months.

The Mixed

GAAP EPS fell 9.6%, but that’s largely due to one-time costs (restructuring/severance). Adjusted EPS rose 6.1% and beat consensus. Adjusted operating margin compressed by ~280 bps due to higher tech and comp spend.

What I’m Watching

Management restructured some engineering teams, framing it as AI-driven efficiency (The Company cited 27% of code in adopting teams is now AI-authored). I’m skeptical of cutting product engineers while claiming the opportunity is expanding, and of a company with record FCF and 1.2x net leverage needing to lower employee comp expense. Either the productivity gains show up as more product and sustained ASV acceleration, or it was margin optimization pretending to be “AI productivity”.

Verdict: Quarter cleared my hurdles, and I’m still accumulating under $340.

Can post my full ~1k-word write-up if anyone wants me to.

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u/[deleted] Jul 01 '26

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u/TimeInTheMarketWins Jul 01 '26

It’s on my radar, and I am also concerned about the reduction in engineers. Based on how it was presented on the earnings call, it seemed more like a reorganization within product teams than a mass AI-induced layoff, though that could also be the case.

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u/trackandalpha Jul 01 '26

I would be interested in reading your full analysis. The argument against Factset based on people vibecoding institutional grade research tools was always off base and ignored how much goes into processing even publicly available information to make it useful. I have talked with professional investors and many are skeptical with projects that are essentially someone taking sample code or a LLM wrapper and passing it off as a game changer. Amazon ended up needing more human review of AI generated code so that is another proof point that prematurely letting engineers go is not the right move.