Willis Lease Finance (WLFC) Change in Accured Expenses (2010 - 2026)
Willis Lease Finance (WLFC) posted Change in Accured Expenses of $15.8 million for Q2 2026, down 30.0% from $22.58 million a year earlier.
Willis Lease Finance (WLFC) Change in Accured Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Change in Accured Expenses at Willis Lease Finance was -$1.46 million; for FY2025, it came in at $8.47 million, down 59.1% from FY2024.
- In prior years, Willis Lease Finance's Change in Accured Expenses was $20.7 million in FY2024 (+20.7%), $17.15 million in FY2023, $942,000 in FY2022 and $58,000 in FY2021.
- Quarterly Change in Accured Expenses has run from a low of -$43.34 million in Q2 2024 to a high of $52.18 million in Q1 2024 over five years.
- On a year-over-year basis, Change in Accured Expenses increased in three of the last four quarters, with growth averaging 39.9%.
- The strongest year-over-year quarter for Change in Accured Expenses in the past five years was Q1 2024, with growth of 585.4%; the weakest was Q2 2026, with a decline of 30.0%.
- According to Business Quant data, Change in Accured Expenses for the three prior quarters was -$27.05 million (Q1 2026), $20.94 million (Q4 2025) and -$11.15 million (Q3 2025).
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 | Willis Lease Finance | 965.65 Mn | 967.39 Mn | - | 15.80 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 15.80 Mn |
| Mar 31, 2026 | -27.05 Mn |
| Dec 31, 2025 | 20.94 Mn |
| Sep 30, 2025 | -11.15 Mn |
| Jun 30, 2025 | 22.58 Mn |
| Mar 31, 2025 | -23.90 Mn |
| Dec 31, 2024 | 9.17 Mn |
| Sep 30, 2024 | 2.70 Mn |
| Jun 30, 2024 | -43.34 Mn |
| Mar 31, 2024 | 52.18 Mn |
| Dec 31, 2023 | 8.82 Mn |
| Sep 30, 2023 | 1.72 Mn |
| Jun 30, 2023 | -999,000.00 |
| Mar 31, 2023 | 7.61 Mn |
| Dec 31, 2022 | 2.65 Mn |
| Sep 30, 2022 | -1.66 Mn |
| Jun 30, 2022 | -6.17 Mn |
| Mar 31, 2022 | 6.12 Mn |
| Dec 31, 2021 | -11.24 Mn |
| Sep 30, 2021 | 2.25 Mn |
Willis Lease Finance 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=WLFC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "WLFC", "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=WLFC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();