Factset Research Systems (FDS) Current Assets (2010 - 2026)
Factset Research Systems (FDS) posted Current Assets of $727.52 million for fiscal Q3 2026 (quarter ended May 31, 2026), down 4.3% from $760.48 million a year earlier but up 0.5% from the prior quarter.
Factset Research Systems (FDS) Current Assets (2010 - 2026) Analysis & Trends
At the end of FY2025 (ended Aug 31, 2025), Factset Research Systems' Current Assets came in at $729.76 million, down 12.7% from FY2024.
- Annual Current Assets shows a five-year compound annual growth rate of -2.8% (FY2020 to FY2025).
- In prior fiscal years, Factset Research Systems' Current Assets was $835.85 million in FY2024 (+8.5%), $770.14 million in FY2023 (-11.5%), $870.35 million in FY2022 (-6.8%) and $933.58 million in FY2021 (+10.9%).
- Quarterly Current Assets has run from a low of $707.64 million in fiscal Q2 2025 to a high of $1.09 billion in fiscal Q2 2022 over five years.
- On a year-over-year basis, Current Assets increased in two of the last eight quarters, with an average decline of 4.9%.
- The strongest year-over-year quarter for Current Assets in the past five years was fiscal Q2 2022, with growth of 25.7%; the weakest was fiscal Q2 2023, with a decline of 21.3%.
- According to Business Quant data, Current Assets for the three prior fiscal quarters was $724.18 million (Q2 2026), $708.57 million (Q1 2026) and $729.76 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Current Assets (Qtr) |
|---|---|---|---|---|---|
| 1 | S&P Global | 115.73 Bn | 111.34 Bn | 2.98 Bn | 8.71 Bn |
| 2 | Moodys | 78.77 Bn | 71.20 Bn | 1.67 Bn | 3.98 Bn |
| 3 | Msci | 39.23 Bn | 37.58 Bn | 717.10 Mn | 1.44 Bn |
| 4 | Verisk Analytics | 21.59 Bn | 16.23 Bn | 572.90 Mn | 1.12 Bn |
| 5 | Equifax | 16.56 Bn | 15.96 Bn | 926.40 Mn | 1.58 Bn |
| 6 | TransUnion | 12.32 Bn | 9.30 Bn | - | 2.18 Bn |
| 7 | Factset Research Systems | 9.30 Bn | 8.06 Bn | 310.73 Mn | 727.52 Mn |
| 8 | Morningstar | 6.99 Bn | 4.89 Bn | 423.90 Mn | 1.03 Bn |
| 9 | Mastercard | 490.78 Bn | 450.70 Bn | - | 26.52 Bn |
| 10 | Cme | 94.57 Bn | 94.57 Bn | - | 161.63 Bn |
Historic Data
| Date | Value |
|---|---|
| May 31, 2026 | 727.52 Mn |
| Feb 28, 2026 | 724.18 Mn |
| Nov 30, 2025 | 708.57 Mn |
| Aug 31, 2025 | 729.76 Mn |
| May 31, 2025 | 760.48 Mn |
| Feb 28, 2025 | 707.64 Mn |
| Nov 30, 2024 | 750.70 Mn |
| Aug 31, 2024 | 835.85 Mn |
| May 31, 2024 | 858.28 Mn |
| Feb 29, 2024 | 823.02 Mn |
| Nov 30, 2023 | 765.77 Mn |
| Aug 31, 2023 | 770.14 Mn |
| May 31, 2023 | 844.31 Mn |
| Feb 28, 2023 | 858.65 Mn |
| Nov 30, 2022 | 829.21 Mn |
| Aug 31, 2022 | 870.35 Mn |
| May 31, 2022 | 873.47 Mn |
| Feb 28, 2022 | 1.09 Bn |
| Nov 30, 2021 | 948.57 Mn |
| Aug 31, 2021 | 933.58 Mn |
Factset Research Systems 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=current-assets&ticker=FDS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "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=current-assets&ticker=FDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();