First United (FUNC) Operating Expenses (2010 - 2026)
First United's Operating Expenses was $13.82 million in Q3 2026, up 6.4% from $12.99 million a year earlier but down 12.4% from the prior quarter.
First United (FUNC) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, First United's Operating Expenses was $58.14 million through Sep 30, 2026, up 14.9% year-over-year; for FY2025, it was $53.41 million, up 7.6% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 4.0% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $49.64 million in FY2024 (-1.2%), $50.24 million in FY2023 (+16.5%), $43.13 million in FY2022 (-9.8%) and $47.8 million in FY2021 (+8.8%).
- Quarterly Operating Expenses has moved between $10.33 million (Q3 2022) and $15.77 million (Q2 2026) over five years.
- Compared with a year earlier, Operating Expenses has increased for six straight quarters, with growth averaging 8.3% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q3 2023 (growth of 23.8%); the worst was Q3 2022 (a decline of 20.7%).
- Per Business Quant data, FUNC's Operating Expenses in the three quarters before Q3 2026 was $15.77 million (Q2 2026), $13.69 million (Q1 2026) and $14.87 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 918.91 Bn | 918.91 Bn | - | 27.30 Bn |
| 2 | Banco Santander Chile | 870.35 Bn | 846.93 Bn | - | - |
| 3 | Bank Of America | 358.55 Bn | -2,017.56 Bn | - | 19.72 Bn |
| 4 | Hsbc Holdings | 315.74 Bn | -668.95 Bn | - | - |
| 5 | Morgan Stanley | 290.88 Bn | -253.14 Bn | - | 13.71 Bn |
| 6 | Royal Bank Of Canada | 287.92 Bn | 137.98 Bn | - | 7.02 Bn |
| 7 | Goldman Sachs | 270.57 Bn | -3,472.88 Bn | - | 11.31 Bn |
| 8 | Wells Fargo & Company | 258.79 Bn | 258.79 Bn | - | 13.74 Bn |
| 9 | Mitsubishi Ufj Financial | 247.94 Bn | 129.81 Bn | - | - |
| 10 | First United | 299.30 Mn | -82.22 Mn | - | 13.82 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 13.82 Mn |
| Jun 30, 2026 | 15.77 Mn |
| Mar 31, 2026 | 13.69 Mn |
| Dec 31, 2025 | 14.87 Mn |
| Sep 30, 2025 | 12.99 Mn |
| Jun 30, 2025 | 12.97 Mn |
| Mar 31, 2025 | 12.58 Mn |
| Dec 31, 2024 | 12.08 Mn |
| Sep 30, 2024 | 12.31 Mn |
| Jun 30, 2024 | 12.36 Mn |
| Mar 31, 2024 | 12.88 Mn |
| Dec 31, 2023 | 12.31 Mn |
| Sep 30, 2023 | 12.79 Mn |
| Jun 30, 2023 | 12.51 Mn |
| Mar 31, 2023 | 12.64 Mn |
| Dec 31, 2022 | 11.59 Mn |
| Sep 30, 2022 | 10.33 Mn |
| Jun 30, 2022 | 10.63 Mn |
| Mar 31, 2022 | 10.58 Mn |
| Dec 31, 2021 | 11.22 Mn |
First United Operating 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=operating-expenses&ticker=FUNC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "FUNC", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=FUNC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();