Factset Research Systems (FDS) Long-Term Debt Repayments (2017 - 2026)
Factset Research Systems (FDS) reported Long-Term Debt Repayments of $75 million for fiscal Q3 2026 (quarter ended May 31, 2026), down 86.2% from $542.5 million a year earlier.
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Analysis
Factset Research Systems (FDS) Long-Term Debt Repayments (2017 - 2026) Analysis & Trends
Over the twelve months ended May 31, 2026, Factset Research Systems' Long-Term Debt Repayments came in at $137.5 million, down 82.9% year-over-year; for FY2025 (ended Aug 31, 2025), it was $805 million, up 222.0% from FY2024.
- Long-Term Debt Repayments has a three-year compound annual growth rate of -0.8% (FY2022 to FY2025).
- By fiscal year, Long-Term Debt Repayments came in at $250 million in FY2024 (-33.3%), $375 million in FY2023 (-54.5%) and $825 million in FY2022.
- Five-year quarterly Long-Term Debt Repayments spans a low of $62.5 million in fiscal Q3 2023 and a high of $700 million in fiscal Q3 2022.
- Year over year, Long-Term Debt Repayments gained in two of the last six quarters, with growth averaging 133.6%.
- The high point for year-over-year Long-Term Debt Repayments in five years was fiscal Q3 2025 (growth of 768.0%); the low point was fiscal Q3 2023 (a decline of 91.1%).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | LT Debt Repayment (Qtr) |
|---|---|---|---|---|---|
| 1 | S&P Global | 126.49 Bn | 117.07 Bn | 2.98 Bn | - |
| 2 | Moodys | 83.74 Bn | 76.03 Bn | 1.67 Bn | - |
| 3 | Msci | 40.93 Bn | 39.28 Bn | 717.10 Mn | 225.00 Mn |
| 4 | Verisk Analytics | 24.74 Bn | 19.38 Bn | 572.90 Mn | - |
| 5 | Equifax | 18.74 Bn | 18.01 Bn | 926.40 Mn | 275.00 Mn |
| 6 | TransUnion | 14.06 Bn | 10.88 Bn | - | 23.10 Mn |
| 7 | Factset Research Systems | 10.96 Bn | 9.73 Bn | 310.73 Mn | 75.00 Mn |
| 8 | Morningstar | 7.77 Bn | 5.67 Bn | 423.90 Mn | 84.70 Mn |
| 9 | Mastercard | 544.62 Bn | 504.55 Bn | - | - |
| 10 | Cme | 105.82 Bn | 93.92 Bn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| May 31, 2026 | 75.00 Mn |
| Aug 31, 2025 | 62.50 Mn |
| May 31, 2025 | 542.50 Mn |
| Feb 28, 2025 | 137.50 Mn |
| Nov 30, 2024 | 62.50 Mn |
| Aug 31, 2024 | 62.50 Mn |
| May 31, 2024 | 62.50 Mn |
| Feb 29, 2024 | 62.50 Mn |
| Nov 30, 2023 | 62.50 Mn |
| Aug 31, 2023 | 62.50 Mn |
| May 31, 2023 | 62.50 Mn |
| Feb 28, 2023 | 125.00 Mn |
| Nov 30, 2022 | 125.00 Mn |
| Aug 31, 2022 | 125.00 Mn |
| May 31, 2022 | 700.00 Mn |
| Aug 31, 2017 | 65.00 Mn |
API Access
Factset Research Systems Long-Term Debt Repayments 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=long-term-debt-repayments&ticker=FDS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "long-term-debt-repayments", "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=long-term-debt-repayments&ticker=FDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();