Factset Research Systems (FDS) Dividends payables (2010 - 2026)
Factset Research Systems' Dividends payables was $41.5 million in fiscal Q3 2026 (quarter ended May 31, 2026), down 0.3% from $41.64 million a year earlier but up 3.0% from the prior quarter.
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Analysis
Factset Research Systems (FDS) Dividends payables (2010 - 2026) Analysis & Trends
At the end of FY2025 (ended Aug 31, 2025), Dividends payables at Factset Research Systems came in at $41.41 million, up 4.9% from FY2024.
- Dividends payables has now increased for 15 consecutive fiscal years, with a five-year compound annual growth rate of 7.2% (FY2020 to FY2025).
- In earlier fiscal years, Dividends payables was $39.47 million in FY2024 (+5.9%), $37.27 million in FY2023 (+10.1%), $33.86 million in FY2022 (+9.8%) and $30.85 million in FY2021 (+5.3%).
- Quarterly Dividends payables has moved between $30.85 million (fiscal Q4 2021) and $41.64 million (fiscal Q3 2025) over five years.
- Compared with a year earlier, Dividends payables was higher in seven of the last eight quarters, with growth averaging 4.1%.
- The best year-over-year quarter for Dividends payables over five years was fiscal Q3 2023 (growth of 10.8%); the worst was fiscal Q3 2026 (a decline of 0.3%).
- Per Business Quant data, FDS's Dividends payables in the three fiscal quarters before Q3 2026 was $40.31 million (Q2 2026), $40.97 million (Q1 2026) and $41.41 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Dividends payables (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 | 41.50 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
Download Data
Historic Data
| Date | Value |
|---|---|
| May 31, 2026 | 41.50 Mn |
| Feb 28, 2026 | 40.31 Mn |
| Nov 30, 2025 | 40.97 Mn |
| Aug 31, 2025 | 41.41 Mn |
| May 31, 2025 | 41.64 Mn |
| Feb 28, 2025 | 39.51 Mn |
| Nov 30, 2024 | 39.57 Mn |
| Aug 31, 2024 | 39.47 Mn |
| May 31, 2024 | 39.59 Mn |
| Feb 29, 2024 | 37.36 Mn |
| Nov 30, 2023 | 37.30 Mn |
| Aug 31, 2023 | 37.27 Mn |
| May 31, 2023 | 37.44 Mn |
| Feb 28, 2023 | 34.10 Mn |
| Nov 30, 2022 | 34.01 Mn |
| Aug 31, 2022 | 33.86 Mn |
| May 31, 2022 | 33.80 Mn |
| Feb 28, 2022 | 31.07 Mn |
| Nov 30, 2021 | 30.97 Mn |
| Aug 31, 2021 | 30.85 Mn |
API Access
Factset Research Systems Dividends payables 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=dividends-payables&ticker=FDS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "dividends-payables", "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=dividends-payables&ticker=FDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();