Factset Research Systems (FDS) Non-Current Assets (2010 - 2026)
Factset Research Systems' Non-Current Assets came in at $3.49 billion for fiscal Q4 2026 (quarter ended Aug 31, 2026), down 2.4% from $3.57 billion a year earlier but up 0.7% from the prior quarter.
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Analysis
Factset Research Systems (FDS) Non-Current Assets (2010 - 2026) Analysis & Trends
Going back to fiscal Q4 2010, Factset Research Systems' Non-Current Assets data covers 65 quarters.
- Non-Current Assets carries a five-year compound annual growth rate of 22.0% (FY2021 to FY2026).
- Going back by fiscal year, Non-Current Assets was $3.57 billion in FY2025 (+11.0%), $3.22 billion in FY2024 (+0.8%), $3.19 billion in FY2023 (+1.6%) and $3.14 billion in FY2022 (+143.5%).
- The five-year range for quarterly Non-Current Assets is $1.28 billion (fiscal Q2 2022) to $3.58 billion (fiscal Q3 2025).
- Year-over-year, Non-Current Assets has declined for three consecutive quarters, with growth averaging 4.8% over the last eight quarters.
- The fastest year-over-year change in Non-Current Assets over five years came in fiscal Q3 2022 (growth of 146.1%), and the weakest in fiscal Q3 2026 (a decline of 3.2%).
- Business Quant data shows FDS's Non-Current Assets at $3.46 billion (Q3 2026), $3.5 billion (Q2 2026) and $3.51 billion (Q1 2026) in the three fiscal quarters before Q4 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Non-Current Assets (Qtr) |
|---|---|---|---|---|---|
| 1 | S&P Global | 136.14 Bn | 125.99 Bn | 2.64 Bn | 41.62 Bn |
| 2 | Moodys | 87.37 Bn | 80.29 Bn | 1.50 Bn | 10.61 Bn |
| 3 | Msci | 46.53 Bn | 45.01 Bn | 739.80 Mn | 4.30 Bn |
| 4 | Verisk Analytics | 25.76 Bn | 20.40 Bn | 572.90 Mn | 3.37 Bn |
| 5 | Equifax | 21.57 Bn | 20.84 Bn | 940.10 Mn | 10.35 Bn |
| 6 | TransUnion | 15.42 Bn | 12.11 Bn | - | 9.89 Bn |
| 7 | Factset Research Systems | 11.51 Bn | 10.36 Bn | 308.40 Mn | 3.49 Bn |
| 8 | Morningstar | 9.02 Bn | 6.91 Bn | 431.40 Mn | 2.89 Bn |
| 9 | Mastercard | 571.76 Bn | 531.85 Bn | - | 33.67 Bn |
| 10 | Cme | 109.34 Bn | 97.67 Bn | - | 32.95 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 31, 2026 | 3.49 Bn |
| May 31, 2026 | 3.46 Bn |
| Feb 28, 2026 | 3.50 Bn |
| Nov 30, 2025 | 3.51 Bn |
| Aug 31, 2025 | 3.57 Bn |
| May 31, 2025 | 3.58 Bn |
| Feb 28, 2025 | 3.53 Bn |
| Nov 30, 2024 | 3.30 Bn |
| Aug 31, 2024 | 3.22 Bn |
| May 31, 2024 | 3.18 Bn |
| Feb 29, 2024 | 3.17 Bn |
| Nov 30, 2023 | 3.19 Bn |
| Aug 31, 2023 | 3.19 Bn |
| May 31, 2023 | 3.15 Bn |
| Feb 28, 2023 | 3.14 Bn |
| Nov 30, 2022 | 3.15 Bn |
| Aug 31, 2022 | 3.14 Bn |
| May 31, 2022 | 3.20 Bn |
| Feb 28, 2022 | 1.28 Bn |
| Nov 30, 2021 | 1.31 Bn |
API Access
Factset Research Systems Non-Current Assets 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=non-current-assets&ticker=FDS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "non-current-assets", "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=non-current-assets&ticker=FDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();