Factset Research Systems (FDS) Other Non-Current Liabilities (2010 - 2026)
Factset Research Systems' Other Non-Current Liabilities was $41.32 million in fiscal Q3 2026 (quarter ended May 31, 2026), down 14.1% from $48.07 million a year earlier and down 0.2% from the prior quarter.
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Analysis
Factset Research Systems (FDS) Other Non-Current Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025 (ended Aug 31, 2025), Other Non-Current Liabilities at Factset Research Systems came in at $45.1 million, up 11.5% from FY2024.
- Other Non-Current Liabilities shows a five-year compound annual growth rate of 10.2% (FY2020 to FY2025).
- In earlier fiscal years, Other Non-Current Liabilities was $40.45 million in FY2024 (+33.3%), $30.34 million in FY2023 (-11.3%), $34.21 million in FY2022 (+13.0%) and $30.28 million in FY2021 (+9.2%).
- The fiscal Q3 2026 figure marks the lowest quarterly Other Non-Current Liabilities since fiscal Q4 2024.
- Compared with a year earlier, Other Non-Current Liabilities was higher in six of the last eight quarters, with growth averaging 15.1%.
- The best year-over-year quarter for Other Non-Current Liabilities over five years was fiscal Q1 2025 (growth of 34.0%); the worst was fiscal Q3 2026 (a decline of 14.1%).
- Per Business Quant data, FDS's Other Non-Current Liabilities in the three fiscal quarters before Q3 2026 was $41.39 million (Q2 2026), $44.51 million (Q1 2026) and $45.1 million (Q4 2025).
Peer Set
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
Download Data
Historic Data
| Date | Value |
|---|---|
| May 31, 2026 | 41.32 Mn |
| Feb 28, 2026 | 41.39 Mn |
| Nov 30, 2025 | 44.51 Mn |
| Aug 31, 2025 | 45.10 Mn |
| May 31, 2025 | 48.07 Mn |
| Feb 28, 2025 | 46.31 Mn |
| Nov 30, 2024 | 41.90 Mn |
| Aug 31, 2024 | 40.45 Mn |
| May 31, 2024 | 36.75 Mn |
| Feb 29, 2024 | 35.73 Mn |
| Nov 30, 2023 | 31.26 Mn |
| Aug 31, 2023 | 30.34 Mn |
| May 31, 2023 | 36.45 Mn |
| Feb 28, 2023 | 34.83 Mn |
| Nov 30, 2022 | 35.33 Mn |
| Aug 31, 2022 | 34.21 Mn |
| May 31, 2022 | 29.10 Mn |
| Feb 28, 2022 | 31.00 Mn |
| Nov 30, 2021 | 31.31 Mn |
| Aug 31, 2021 | 30.28 Mn |
API Access
Factset Research Systems Other Non-Current Liabilities 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-non-current-liabilities&ticker=FDS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-non-current-liabilities", "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-non-current-liabilities&ticker=FDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();