Factset Research Systems (FDS) Total Current Liabilities (2010 - 2026)
Factset Research Systems' Total Current Liabilities was $1.06 billion in fiscal Q3 2026 (quarter ended May 31, 2026), up 105.2% from $518.92 million a year earlier and up 110.4% from the prior quarter.
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Analysis
Factset Research Systems (FDS) Total Current Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025 (ended Aug 31, 2025), Total Current Liabilities at Factset Research Systems came in at $521.31 million, down 21.9% from FY2024.
- Total Current Liabilities shows a five-year compound annual growth rate of 13.5% (FY2020 to FY2025).
- In earlier fiscal years, Total Current Liabilities was $667.07 million in FY2024 (+37.8%), $484.25 million in FY2023 (+10.5%), $438.29 million in FY2022 (+38.8%) and $315.71 million in FY2021 (+14.3%).
- The fiscal Q3 2026 figure marks the highest quarterly Total Current Liabilities in data going back to fiscal Q4 2010.
- Compared with a year earlier, Total Current Liabilities was higher in five of the last eight quarters, with growth averaging 13.9%.
- The best year-over-year quarter for Total Current Liabilities over five years was fiscal Q3 2026 (growth of 105.2%); the worst was fiscal Q3 2025 (a decline of 22.7%).
- Per Business Quant data, FDS's Total Current Liabilities in the three fiscal quarters before Q3 2026 was $505.93 million (Q2 2026), $458.77 million (Q1 2026) and $521.31 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | S&P Global | 116.38 Bn | 111.98 Bn | 2.98 Bn | 9.13 Bn |
| 2 | Moodys | 78.67 Bn | 71.10 Bn | 1.67 Bn | 3.35 Bn |
| 3 | Msci | 39.16 Bn | 37.50 Bn | 717.10 Mn | 1.61 Bn |
| 4 | Verisk Analytics | 21.84 Bn | 16.48 Bn | 572.90 Mn | 1.12 Bn |
| 5 | Equifax | 16.14 Bn | 15.54 Bn | 926.40 Mn | 2.63 Bn |
| 6 | TransUnion | 11.72 Bn | 8.70 Bn | - | 1.15 Bn |
| 7 | Factset Research Systems | 9.66 Bn | 8.43 Bn | 310.73 Mn | 1.06 Bn |
| 8 | Morningstar | 7.13 Bn | 5.03 Bn | 423.90 Mn | 980.30 Mn |
| 9 | Mastercard | 480.27 Bn | 440.19 Bn | - | 25.00 Bn |
| 10 | Cme | 94.12 Bn | 94.12 Bn | - | 158.72 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| May 31, 2026 | 1.06 Bn |
| Feb 28, 2026 | 505.93 Mn |
| Nov 30, 2025 | 458.77 Mn |
| Aug 31, 2025 | 521.31 Mn |
| May 31, 2025 | 518.92 Mn |
| Feb 28, 2025 | 481.83 Mn |
| Nov 30, 2024 | 538.14 Mn |
| Aug 31, 2024 | 667.07 Mn |
| May 31, 2024 | 671.51 Mn |
| Feb 29, 2024 | 459.75 Mn |
| Nov 30, 2023 | 455.89 Mn |
| Aug 31, 2023 | 484.25 Mn |
| May 31, 2023 | 400.94 Mn |
| Feb 28, 2023 | 410.81 Mn |
| Nov 30, 2022 | 384.02 Mn |
| Aug 31, 2022 | 438.29 Mn |
| May 31, 2022 | 412.72 Mn |
| Feb 28, 2022 | 293.24 Mn |
| Nov 30, 2021 | 272.56 Mn |
| Aug 31, 2021 | 315.71 Mn |
API Access
Factset Research Systems Total 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=total-current-liabilities&ticker=FDS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-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=total-current-liabilities&ticker=FDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();