Materialise (MTLS) Change in Accured Expenses (2019 - 2026)
Materialise (MTLS) reported Change in Accured Expenses of $139,319 for the quarter ended Mar 31, 2026, compared with -$3.72 million a year earlier.
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Analysis
Materialise (MTLS) Change in Accured Expenses (2019 - 2026) Analysis & Trends
Over the twelve months ended Mar 31, 2026, Materialise's Change in Accured Expenses came in at -$1.47 million; for the year ended Dec 31, 2025, it was -$5.65 million.
- By year, Change in Accured Expenses came in at -$1.38 million in the year ended Dec 31, 2024, -$9.12 million in the year ended Dec 31, 2023, $12.62 million in the year ended Dec 31, 2022 (+199.9%) and $4.21 million in the year ended Dec 31, 2021 (+532.0%).
- Five-year quarterly Change in Accured Expenses spans a low of -$4.45 million in the quarter ended Mar 31, 2023 and a high of $9.36 million in the quarter ended Jun 30, 2022.
- Per Business Quant data, the three quarters before the quarter ended Mar 31, 2026 came in at -$918,430 (quarter ended Dec 31, 2025), $2.41 million (quarter ended Sep 30, 2025) and -$3.1 million (quarter ended Jun 30, 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 456.65 Bn | 425.71 Bn | 1.64 Bn | 7.31 Mn |
| 2 | Oracle | 417.55 Bn | 290.11 Bn | - | -1.08 Bn |
| 3 | Sap Se | 259.04 Bn | 180.13 Bn | 8.40 Bn | - |
| 4 | Salesforce | 194.78 Bn | 150.65 Bn | 8.70 Bn | 891.00 Mn |
| 5 | ServiceNow | 142.47 Bn | 120.93 Bn | 2.82 Bn | 280.00 Mn |
| 6 | Automatic Data Processing | 105.00 Bn | 87.13 Bn | 2.51 Bn | 200.00 Mn |
| 7 | Intuit | 75.89 Bn | 55.24 Bn | 3.44 Bn | 304.00 Mn |
| 8 | Relx | 60.92 Bn | 57.89 Bn | - | - |
| 9 | Strategy | 56.49 Bn | 49.48 Bn | 81.55 Mn | -2.04 Mn |
| 10 | Materialise | 502.07 Mn | 501.97 Mn | 46.23 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2026 | 139,318.73 |
| Dec 31, 2025 | -918,430.33 |
| Sep 30, 2025 | 2.41 Mn |
| Jun 30, 2025 | -3.10 Mn |
| Mar 31, 2025 | -3.72 Mn |
| Dec 31, 2024 | -758,702.73 |
| Sep 30, 2024 | 2.32 Mn |
| Jun 30, 2024 | 684,900.50 |
| Mar 31, 2024 | -3.60 Mn |
| Dec 31, 2023 | -1.24 Mn |
| Sep 30, 2023 | -1.49 Mn |
| Jun 30, 2023 | -1.93 Mn |
| Mar 31, 2023 | -4.45 Mn |
| Dec 31, 2022 | 2.58 Mn |
| Sep 30, 2022 | 1.97 Mn |
| Jun 30, 2022 | 9.36 Mn |
| Mar 31, 2022 | -1.00 Mn |
| Dec 31, 2021 | -1.48 Mn |
| Sep 30, 2021 | 4.25 Mn |
| Jun 30, 2021 | 1.02 Mn |
API Access
Materialise Change in Accured Expenses 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=change-in-accured-expenses&ticker=MTLS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "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=change-in-accured-expenses&ticker=MTLS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();