Factset Research Systems (FDS) Payables (2010 - 2026)
Factset Research Systems (FDS) posted Payables of $177.01 million for fiscal Q4 2026 (quarter ended Aug 31, 2026), up 0.2% from $176.67 million a year earlier but down 13.9% from the prior quarter.
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Analysis
Factset Research Systems (FDS) Payables (2010 - 2026) Analysis & Trends
Since fiscal Q4 2010, Factset Research Systems has reported Payables for 65 quarters.
- Annual Payables shows a five-year compound annual growth rate of 8.7% (FY2021 to FY2026).
- In prior fiscal years, Factset Research Systems' Payables was $176.67 million in FY2025 (-18.9%), $217.72 million in FY2024 (+36.9%), $159.08 million in FY2023 (+11.8%) and $142.26 million in FY2022 (+22.0%).
- Quarterly Payables has run from a low of $121.33 million in fiscal Q2 2022 to a high of $217.72 million in fiscal Q4 2024 over five years.
- On a year-over-year basis, Payables has increased in each of the last three quarters, with growth averaging 1.5% over the last eight quarters.
- 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 $205.48 million (Q3 2026), $189.55 million (Q2 2026) and $190.25 million (Q1 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Payables (Qtr) |
|---|---|---|---|---|---|
| 1 | S&P Global | 136.14 Bn | 125.99 Bn | 2.64 Bn | 507.00 Mn |
| 2 | Moodys | 87.37 Bn | 80.29 Bn | 1.50 Bn | 1.22 Bn |
| 3 | Msci | 46.53 Bn | 45.01 Bn | 739.80 Mn | 5.90 Mn |
| 4 | Verisk Analytics | 25.76 Bn | 20.40 Bn | 572.90 Mn | 254.30 Mn |
| 5 | Equifax | 21.57 Bn | 20.84 Bn | 940.10 Mn | 115.30 Mn |
| 6 | TransUnion | 15.42 Bn | 12.11 Bn | - | 409.20 Mn |
| 7 | Factset Research Systems | 11.51 Bn | 10.36 Bn | 308.40 Mn | 177.01 Mn |
| 8 | Morningstar | 9.02 Bn | 6.91 Bn | 431.40 Mn | 119.90 Mn |
| 9 | Mastercard | 571.76 Bn | 531.85 Bn | - | 1.08 Bn |
| 10 | Cme | 109.34 Bn | 97.67 Bn | - | 67.70 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 31, 2026 | 177.01 Mn |
| 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 |
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();