Factset Research Systems (FDS) Other Operating Expenses (2009 - 2026)
Factset Research Systems (FDS) posted Other Operating Expenses of $312.19 million for fiscal Q3 2026 (quarter ended May 31, 2026), up 11.2% from $280.73 million a year earlier and up 5.2% from the prior quarter.
Factset Research Systems (FDS) Other Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through May 31, 2026, Other Operating Expenses at Factset Research Systems was $1.19 billion, up 11.1% year-over-year; for FY2025 (ended Aug 31, 2025), it was $1.1 billion, up 8.5% from FY2024.
- Annual Other Operating Expenses has increased for 15 consecutive fiscal years, with a five-year compound annual growth rate of 9.0% (FY2020 to FY2025).
- In prior fiscal years, Factset Research Systems' Other Operating Expenses was $1.01 billion in FY2024 (+4.0%), $973.23 million in FY2023 (+4.0%), $935.38 million in FY2022 (+18.9%) and $786.4 million in FY2021 (+10.5%).
- The fiscal Q3 2026 figure stands as the highest quarterly Other Operating Expenses in data going back to fiscal Q1 2010.
- On a year-over-year basis, Other Operating Expenses has increased in each of the last seven quarters, with growth averaging 8.1% over the last eight quarters.
- The strongest year-over-year quarter for Other Operating Expenses in the past five years was fiscal Q3 2022, with growth of 32.3%; the weakest was fiscal Q3 2023, with a decline of 10.9%.
- According to Business Quant data, Other Operating Expenses for the three prior fiscal quarters was $296.74 million (Q2 2026), $287.92 million (Q1 2026) and $288.67 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | S&P Global | 116.38 Bn | 111.98 Bn | 2.98 Bn |
| 2 | Moodys | 78.67 Bn | 71.10 Bn | 1.67 Bn |
| 3 | Msci | 39.16 Bn | 37.50 Bn | 717.10 Mn |
| 4 | Verisk Analytics | 21.84 Bn | 16.48 Bn | 572.90 Mn |
| 5 | Equifax | 16.14 Bn | 15.54 Bn | 926.40 Mn |
| 6 | TransUnion | 11.72 Bn | 8.70 Bn | - |
| 7 | Factset Research Systems | 9.66 Bn | 8.43 Bn | 310.73 Mn |
| 8 | Morningstar | 7.13 Bn | 5.03 Bn | 423.90 Mn |
| 9 | Mastercard | 480.27 Bn | 440.19 Bn | - |
| 10 | Cme | 94.12 Bn | 94.12 Bn | - |
Historic Data
| Date | Value |
|---|---|
| May 31, 2026 | 312.19 Mn |
| Feb 28, 2026 | 296.74 Mn |
| Nov 30, 2025 | 287.92 Mn |
| Aug 31, 2025 | 288.67 Mn |
| May 31, 2025 | 280.73 Mn |
| Feb 28, 2025 | 269.60 Mn |
| Nov 30, 2024 | 258.78 Mn |
| Aug 31, 2024 | 258.20 Mn |
| May 31, 2024 | 246.99 Mn |
| Feb 29, 2024 | 255.14 Mn |
| Nov 30, 2023 | 251.62 Mn |
| Aug 31, 2023 | 262.52 Mn |
| May 31, 2023 | 242.13 Mn |
| Feb 28, 2023 | 241.25 Mn |
| Nov 30, 2022 | 227.32 Mn |
| Aug 31, 2022 | 243.23 Mn |
| May 31, 2022 | 271.62 Mn |
| Feb 28, 2022 | 209.71 Mn |
| Nov 30, 2021 | 210.83 Mn |
| Aug 31, 2021 | 197.53 Mn |
Factset Research Systems Other Operating Expenses 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=other-operating-expenses&ticker=FDS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-operating-expenses", "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=other-operating-expenses&ticker=FDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();