Factset Research Systems (FDS) Payables (2010 - 2026)
Factset Research Systems (FDS) posted Payables of $205.48 million for fiscal Q3 2026 (quarter ended May 31, 2026), up 10.4% from $186.13 million a year earlier and up 8.4% from the prior quarter.
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Analysis
Factset Research Systems (FDS) Payables (2010 - 2026) Analysis & Trends
At the end of FY2025 (ended Aug 31, 2025), Factset Research Systems' Payables came in at $176.67 million, down 18.9% from FY2024.
- Annual Payables shows a five-year compound annual growth rate of 9.7% (FY2020 to FY2025).
- In prior fiscal years, Factset Research Systems' Payables was $217.72 million in FY2024 (+36.9%), $159.08 million in FY2023 (+11.8%), $142.26 million in FY2022 (+22.0%) and $116.62 million in FY2021 (+4.7%).
- The fiscal Q3 2026 figure stands as the highest quarterly Payables since fiscal Q4 2024.
- On a year-over-year basis, Payables increased in six of the last eight quarters, with growth averaging 6.1%.
- The strongest year-over-year quarter for Payables in the past five years was fiscal Q4 2024, with growth of 36.9%; the weakest was fiscal Q4 2025, with a decline of 18.9%.
- According to Business Quant data, Payables for the three prior fiscal quarters was $189.55 million (Q2 2026), $190.25 million (Q1 2026) and $176.67 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Payables (Qtr) |
|---|---|---|---|---|---|
| 1 | S&P Global | 116.38 Bn | 111.98 Bn | 2.98 Bn | 611.00 Mn |
| 2 | Moodys | 78.67 Bn | 71.10 Bn | 1.67 Bn | 1.09 Bn |
| 3 | Msci | 39.16 Bn | 37.50 Bn | 717.10 Mn | 17.20 Mn |
| 4 | Verisk Analytics | 21.84 Bn | 16.48 Bn | 572.90 Mn | 254.30 Mn |
| 5 | Equifax | 16.14 Bn | 15.54 Bn | 926.40 Mn | 126.60 Mn |
| 6 | TransUnion | 11.72 Bn | 8.70 Bn | - | 404.90 Mn |
| 7 | Factset Research Systems | 9.66 Bn | 8.43 Bn | 310.73 Mn | 205.48 Mn |
| 8 | Morningstar | 7.13 Bn | 5.03 Bn | 423.90 Mn | 110.10 Mn |
| 9 | Mastercard | 480.27 Bn | 440.19 Bn | - | 1.13 Bn |
| 10 | Cme | 94.12 Bn | 94.12 Bn | - | 68.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| May 31, 2026 | 205.48 Mn |
| Feb 28, 2026 | 189.55 Mn |
| Nov 30, 2025 | 190.25 Mn |
| Aug 31, 2025 | 176.67 Mn |
| May 31, 2025 | 186.13 Mn |
| Feb 28, 2025 | 170.61 Mn |
| Nov 30, 2024 | 190.87 Mn |
| Aug 31, 2024 | 217.72 Mn |
| May 31, 2024 | 177.97 Mn |
| Feb 29, 2024 | 165.52 Mn |
| Nov 30, 2023 | 187.49 Mn |
| Aug 31, 2023 | 159.08 Mn |
| May 31, 2023 | 147.72 Mn |
| Feb 28, 2023 | 154.32 Mn |
| Nov 30, 2022 | 156.72 Mn |
| Aug 31, 2022 | 142.26 Mn |
| May 31, 2022 | 134.11 Mn |
| Feb 28, 2022 | 121.33 Mn |
| Nov 30, 2021 | 136.45 Mn |
| Aug 31, 2021 | 116.62 Mn |
API Access
Factset Research Systems 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=payables&ticker=FDS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "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=payables&ticker=FDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();