Factset Research Systems (FDS) Total Liabilities (2010 - 2026)
Factset Research Systems' Total Liabilities was $2.14 billion in fiscal Q4 2026 (quarter ended Aug 31, 2026), up 1.0% from $2.12 billion a year earlier but down 1.0% from the prior quarter.
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Analysis
Factset Research Systems (FDS) Total Liabilities (2010 - 2026) Analysis & Trends
From fiscal Q4 2010 onward, Factset Research Systems has reported Total Liabilities for 65 quarters.
- Total Liabilities shows a five-year compound annual growth rate of 12.1% (FY2021 to FY2026).
- In earlier fiscal years, Total Liabilities was $2.12 billion in FY2025 (-1.2%), $2.14 billion in FY2024 (-8.6%), $2.34 billion in FY2023 (-12.7%) and $2.68 billion in FY2022 (+122.0%).
- Quarterly Total Liabilities has moved between $1.16 billion (fiscal Q1 2022) and $2.8 billion (fiscal Q3 2022) over five years.
- Compared with a year earlier, Total Liabilities was higher in two of the last eight quarters, with an average decline of 1.6%.
- The best year-over-year quarter for Total Liabilities over five years was fiscal Q3 2022 (growth of 135.9%); the worst was fiscal Q3 2023 (a decline of 16.8%).
- Per Business Quant data, FDS's Total Liabilities in the three fiscal quarters before Q4 2026 was $2.16 billion (Q3 2026), $2.09 billion (Q2 2026) and $2.05 billion (Q1 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | S&P Global | 136.14 Bn | 125.99 Bn | 2.64 Bn | 28.20 Bn |
| 2 | Moodys | 87.37 Bn | 80.29 Bn | 1.50 Bn | 11.42 Bn |
| 3 | Msci | 46.53 Bn | 45.01 Bn | 739.80 Mn | 8.61 Bn |
| 4 | Verisk Analytics | 25.76 Bn | 20.40 Bn | 572.90 Mn | 5.68 Bn |
| 5 | Equifax | 21.57 Bn | 20.84 Bn | 940.10 Mn | 7.44 Bn |
| 6 | TransUnion | 15.42 Bn | 12.11 Bn | - | 7.09 Bn |
| 7 | Factset Research Systems | 11.51 Bn | 10.36 Bn | 308.40 Mn | 2.14 Bn |
| 8 | Morningstar | 9.02 Bn | 6.91 Bn | 431.40 Mn | 2.93 Bn |
| 9 | Mastercard | 571.76 Bn | 531.85 Bn | - | 51.40 Bn |
| 10 | Cme | 109.34 Bn | 97.67 Bn | - | 165.53 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 31, 2026 | 2.14 Bn |
| May 31, 2026 | 2.16 Bn |
| Feb 28, 2026 | 2.09 Bn |
| Nov 30, 2025 | 2.05 Bn |
| Aug 31, 2025 | 2.12 Bn |
| May 31, 2025 | 2.18 Bn |
| Feb 28, 2025 | 2.18 Bn |
| Nov 30, 2024 | 2.06 Bn |
| Aug 31, 2024 | 2.14 Bn |
| May 31, 2024 | 2.15 Bn |
| Feb 29, 2024 | 2.19 Bn |
| Nov 30, 2023 | 2.25 Bn |
| Aug 31, 2023 | 2.34 Bn |
| May 31, 2023 | 2.33 Bn |
| Feb 28, 2023 | 2.39 Bn |
| Nov 30, 2022 | 2.50 Bn |
| Aug 31, 2022 | 2.68 Bn |
| May 31, 2022 | 2.80 Bn |
| Feb 28, 2022 | 1.16 Bn |
| Nov 30, 2021 | 1.16 Bn |
API Access
Factset Research Systems Total 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-liabilities&ticker=FDS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-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-liabilities&ticker=FDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();