Factset Research Systems (FDS) Prepaid Assets (2010 - 2026)
Factset Research Systems' Prepaid Assets was $58.33 million in fiscal Q3 2026 (quarter ended May 31, 2026), down 8.2% from $63.53 million a year earlier and down 35.2% from the prior quarter.
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Analysis
Factset Research Systems (FDS) Prepaid Assets (2010 - 2026) Analysis & Trends
At the end of FY2025 (ended Aug 31, 2025), Prepaid Assets at Factset Research Systems came in at $33.6 million, down 44.1% from FY2024.
- Prepaid Assets shows a five-year compound annual growth rate of -5.1% (FY2020 to FY2025).
- In earlier fiscal years, Prepaid Assets was $60.09 million in FY2024 (+18.7%), $50.61 million in FY2023 (-44.5%), $91.21 million in FY2022 (+80.2%) and $50.63 million in FY2021 (+15.9%).
- Quarterly Prepaid Assets has moved between $33.6 million (fiscal Q4 2025) and $100.85 million (fiscal Q1 2026) over five years.
- Compared with a year earlier, Prepaid Assets was higher in six of the last eight quarters, with growth averaging 15.2%.
- The best year-over-year quarter for Prepaid Assets over five years was fiscal Q4 2022 (growth of 80.2%); the worst was fiscal Q1 2024 (a decline of 49.1%).
- Per Business Quant data, FDS's Prepaid Assets in the three fiscal quarters before Q3 2026 was $90 million (Q2 2026), $100.85 million (Q1 2026) and $33.6 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 | 58.33 Mn |
| Feb 28, 2026 | 90.00 Mn |
| Nov 30, 2025 | 100.85 Mn |
| Aug 31, 2025 | 33.60 Mn |
| May 31, 2025 | 63.53 Mn |
| Feb 28, 2025 | 75.93 Mn |
| Nov 30, 2024 | 78.68 Mn |
| Aug 31, 2024 | 60.09 Mn |
| May 31, 2024 | 51.73 Mn |
| Feb 29, 2024 | 58.05 Mn |
| Nov 30, 2023 | 50.85 Mn |
| Aug 31, 2023 | 50.61 Mn |
| May 31, 2023 | 66.17 Mn |
| Feb 28, 2023 | 82.29 Mn |
| Nov 30, 2022 | 99.83 Mn |
| Aug 31, 2022 | 91.21 Mn |
| May 31, 2022 | 55.07 Mn |
| Feb 28, 2022 | 57.79 Mn |
| Nov 30, 2021 | 58.45 Mn |
| Aug 31, 2021 | 50.63 Mn |
API Access
Factset Research Systems Prepaid 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=prepaid-assets&ticker=FDS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "prepaid-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=prepaid-assets&ticker=FDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();