Albany International (AIN) Change in Accured Expenses (2010 - 2026)
Albany International's Change in Accured Expenses was -$21.16 million in Q2 2026, compared with -$2.15 million a year earlier.
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Analysis
Albany International (AIN) Change in Accured Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Albany International's Change in Accured Expenses was $8.03 million through Jun 30, 2026; for FY2025, it came in at $7.98 million.
- In earlier years, Change in Accured Expenses was -$1.28 million in FY2024, -$10.44 million in FY2023, $3.23 million in FY2022 and -$774,000 in FY2021.
- The Q2 2026 figure marks the lowest quarterly Change in Accured Expenses since Q1 2025.
- Compared with a year earlier, Change in Accured Expenses was higher in three of the last four quarters, with growth averaging 74.8%.
- The best year-over-year quarter for Change in Accured Expenses over five years was Q2 2024 (growth of 370.5%); the worst was Q3 2025 (a decline of 93.9%).
- Per Business Quant data, AIN's Change in Accured Expenses in the three quarters before Q2 2026 was -$2.1 million (Q1 2026), $30.86 million (Q4 2025) and $427,000 (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 321.31 Bn | 275.31 Bn | 4.68 Bn | - |
| 2 | Rtx | 248.97 Bn | 222.19 Bn | 5.13 Bn | 2.10 Bn |
| 3 | Boeing | 152.99 Bn | 59.70 Bn | 2.41 Bn | 190.00 Mn |
| 4 | Lockheed Martin | 116.67 Bn | 103.39 Bn | 2.45 Bn | - |
| 5 | Howmet Aerospace | 92.54 Bn | 88.15 Bn | 951.00 Mn | 41.00 Mn |
| 6 | General Dynamics | 89.31 Bn | 76.42 Bn | 2.18 Bn | - |
| 7 | Motorola Solutions | 74.04 Bn | 70.40 Bn | 1.68 Bn | 82.00 Mn |
| 8 | Northrop Grumman | 67.90 Bn | 57.15 Bn | 2.12 Bn | -34.00 Mn |
| 9 | Honeywell International | 67.82 Bn | 20.27 Bn | 3.65 Bn | 895.00 Mn |
| 10 | Albany International | 1.73 Bn | 1.31 Bn | 107.90 Mn | -21.16 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -21.16 Mn |
| Mar 31, 2026 | -2.10 Mn |
| Dec 31, 2025 | 30.86 Mn |
| Sep 30, 2025 | 427,000.00 |
| Jun 30, 2025 | -2.15 Mn |
| Mar 31, 2025 | -21.16 Mn |
| Dec 31, 2024 | 7.05 Mn |
| Sep 30, 2024 | 7.05 Mn |
| Jun 30, 2024 | 7.37 Mn |
| Mar 31, 2024 | -22.74 Mn |
| Dec 31, 2023 | 6.01 Mn |
| Sep 30, 2023 | 5.12 Mn |
| Jun 30, 2023 | 1.57 Mn |
| Mar 31, 2023 | -23.14 Mn |
| Dec 31, 2022 | 15.85 Mn |
| Sep 30, 2022 | -879,000.00 |
| Jun 30, 2022 | 7.61 Mn |
| Mar 31, 2022 | -19.35 Mn |
| Dec 31, 2021 | 11.54 Mn |
| Sep 30, 2021 | 5.11 Mn |
API Access
Albany International 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=AIN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "AIN", "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=AIN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();