Materialise (MTLS) Long-Term Debt Repayments (2014 - 2026)
Materialise's Long-Term Debt Repayments was -$3.87 million in the quarter ended Sep 30, 2026, compared with -$4.21 million a year earlier.
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Analysis
Materialise (MTLS) Long-Term Debt Repayments (2014 - 2026) Analysis & Trends
On a trailing twelve-month basis, Materialise's Long-Term Debt Repayments was $16.55 million through Sep 30, 2026, down 35.1% year-over-year; for the year ended Dec 31, 2025, it was $12.49 million, down 50.4% from the prior year.
- Long-Term Debt Repayments shows a five-year compound annual growth rate of -4.5% (years ended Dec 2020 to Dec 2025).
- In earlier years, Long-Term Debt Repayments was $25.18 million in the year ended Dec 31, 2024 (+39.2%), $18.09 million in the year ended Dec 31, 2023 (-3.1%), $18.66 million in the year ended Dec 31, 2022 (+10.5%) and $16.9 million in the year ended Dec 31, 2021 (+7.7%).
- Quarterly Long-Term Debt Repayments has moved between -$6.7 million (the quarter ended Mar 31, 2022) and $37.12 million (the quarter ended Dec 31, 2024) over five years.
- Per Business Quant data, MTLS's Long-Term Debt Repayments in the three quarters before the quarter ended Sep 30, 2026 was -$571,882 (quarter ended Jun 30, 2026), -$4.05 million (quarter ended Mar 31, 2026) and $25.04 million (quarter ended Dec 31, 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | LT Debt Repayment (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 386.60 Bn | 351.42 Bn | 1.93 Bn | - |
| 2 | Oracle | 343.94 Bn | 216.07 Bn | - | 4.20 Bn |
| 3 | Sap Se | 272.35 Bn | 199.75 Bn | 8.64 Bn | -204.78 Mn |
| 4 | Salesforce | 175.46 Bn | 131.33 Bn | 8.70 Bn | 176.00 Mn |
| 5 | Automatic Data Processing | 122.07 Bn | 108.86 Bn | 2.53 Bn | 300,000.00 |
| 6 | ServiceNow | 105.47 Bn | 84.73 Bn | 2.90 Bn | - |
| 7 | Intuit | 94.25 Bn | 73.60 Bn | 3.44 Bn | - |
| 8 | Relx | 73.66 Bn | 72.75 Bn | - | - |
| 9 | Strategy | 51.78 Bn | 38.91 Bn | 89.63 Mn | 449,000.00 |
| 10 | Materialise | 398.11 Mn | -238.44 Mn | 44.91 Mn | -3.87 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | -3.87 Mn |
| Jun 30, 2026 | -571,882.03 |
| Mar 31, 2026 | -4.05 Mn |
| Dec 31, 2025 | 25.04 Mn |
| Sep 30, 2025 | -4.21 Mn |
| Jun 30, 2025 | -2.70 Mn |
| Mar 31, 2025 | -4.70 Mn |
| Dec 31, 2024 | 37.12 Mn |
| Sep 30, 2024 | -5.08 Mn |
| Jun 30, 2024 | -2.12 Mn |
| Mar 31, 2024 | -5.30 Mn |
| Dec 31, 2023 | 33.42 Mn |
| Sep 30, 2023 | -6.22 Mn |
| Jun 30, 2023 | -3.25 Mn |
| Mar 31, 2023 | -6.05 Mn |
| Dec 31, 2022 | 33.56 Mn |
| Sep 30, 2022 | -6.22 Mn |
| Jun 30, 2022 | -3.25 Mn |
| Mar 31, 2022 | -6.70 Mn |
| Dec 31, 2021 | 29.11 Mn |
API Access
Materialise 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=MTLS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "long-term-debt-repayments", "ticker": "MTLS", "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=MTLS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();