Factset Research Systems (FDS) EBIT (2009 - 2026)
Factset Research Systems (FDS) recorded EBIT of $166.3 million in fiscal Q3 2026 (quarter ended May 31, 2026), down 14.3% from $194.16 million a year earlier and down 10.1% from the prior quarter.
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Analysis
Factset Research Systems (FDS) EBIT (2009 - 2026) Analysis & Trends
On a TTM basis, Factset Research Systems' EBIT came in at $720.65 million as of May 31, 2026, up 3.1% year-over-year; for FY2025 (ended Aug 31, 2025), it was $748.3 million, up 6.7% from FY2024.
- Annual EBIT has increased for 12 straight fiscal years, with a five-year compound annual growth rate of 11.2% (FY2020 to FY2025).
- Across earlier fiscal years, EBIT came in at $701.3 million in FY2024 (+11.5%), $629.21 million in FY2023 (+32.3%), $475.48 million in FY2022 (+0.3%) and $474.04 million in FY2021 (+7.8%).
- The fiscal Q3 2026 figure is the lowest quarterly EBIT since fiscal Q4 2024.
- On a year-over-year basis, EBIT rose in five of the last eight quarters, with growth averaging 4.2%.
- Peak year-over-year performance for EBIT in the last five years was growth of 76.8% in fiscal Q3 2023, against a decline of 17.4% in fiscal Q3 2022 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $184.96 million (Q2 2026), $192.07 million (Q1 2026) and $177.32 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBIT (Qtr) |
|---|---|---|---|---|---|
| 1 | S&P Global | 115.73 Bn | 111.34 Bn | 2.98 Bn | 1.81 Bn |
| 2 | Moodys | 78.77 Bn | 71.20 Bn | 1.67 Bn | 1.05 Bn |
| 3 | Msci | 39.23 Bn | 37.58 Bn | 717.10 Mn | 487.50 Mn |
| 4 | Verisk Analytics | 21.59 Bn | 16.23 Bn | 572.90 Mn | 363.70 Mn |
| 5 | Equifax | 16.56 Bn | 15.96 Bn | 926.40 Mn | 314.20 Mn |
| 6 | TransUnion | 12.32 Bn | 9.30 Bn | - | 258.00 Mn |
| 7 | Factset Research Systems | 9.30 Bn | 8.06 Bn | 310.73 Mn | 166.30 Mn |
| 8 | Morningstar | 6.99 Bn | 4.89 Bn | 423.90 Mn | 160.60 Mn |
| 9 | Mastercard | 490.78 Bn | 450.70 Bn | - | 5.59 Bn |
| 10 | Cme | 94.57 Bn | 94.57 Bn | - | 1.11 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| May 31, 2026 | 166.30 Mn |
| Feb 28, 2026 | 184.96 Mn |
| Nov 30, 2025 | 192.07 Mn |
| Aug 31, 2025 | 177.32 Mn |
| May 31, 2025 | 194.16 Mn |
| Feb 28, 2025 | 185.49 Mn |
| Nov 30, 2024 | 191.34 Mn |
| Aug 31, 2024 | 127.86 Mn |
| May 31, 2024 | 202.46 Mn |
| Feb 29, 2024 | 181.94 Mn |
| Nov 30, 2023 | 189.04 Mn |
| Aug 31, 2023 | 116.10 Mn |
| May 31, 2023 | 171.96 Mn |
| Feb 28, 2023 | 169.25 Mn |
| Nov 30, 2022 | 171.90 Mn |
| Aug 31, 2022 | 132.22 Mn |
| May 31, 2022 | 97.25 Mn |
| Feb 28, 2022 | 123.35 Mn |
| Nov 30, 2021 | 122.66 Mn |
| Aug 31, 2021 | 119.18 Mn |
API Access
Factset Research Systems EBIT API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=ebit&ticker=FDS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebit", "ticker": "FDS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=ebit&ticker=FDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();