Orange County Bancorp (OBT) Other Operating Expenses (2020 - 2026)
Orange County Bancorp (OBT) reported Other Operating Expenses of $1.96 million for Q2 2026, down 7.5% from $2.12 million a year earlier but up 4.3% from the prior quarter.
Orange County Bancorp (OBT) Other Operating Expenses (2020 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Orange County Bancorp's Other Operating Expenses came in at $7.55 million, down 9.8% year-over-year; for FY2025, it came in at $7.81 million, up 10.9% from FY2024.
- Other Operating Expenses has increased for three consecutive years, with a five-year compound annual growth rate of 14.1% (FY2020 to FY2025).
- By year, Other Operating Expenses came in at $7.04 million in FY2024 (+39.5%), $5.05 million in FY2023 (+5.1%), $4.8 million in FY2022 (-7.1%) and $5.17 million in FY2021 (+28.0%).
- Five-year quarterly Other Operating Expenses spans a low of $1.12 million in Q1 2022 and a high of $2.71 million in Q4 2024.
- Year over year, Other Operating Expenses has now declined in each of the last three quarters, with growth averaging 23.6% over the last eight quarters.
- The high point for year-over-year Other Operating Expenses in five years was Q4 2024 (growth of 103.1%); the low point was Q4 2022 (a decline of 40.1%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $1.88 million (Q1 2026), $1.93 million (Q4 2025) and $1.79 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Jpmorgan Chase | 879.54 Bn | 909.01 Bn | - |
| 2 | Banco Santander Chile | 418.48 Bn | 538.42 Bn | - |
| 3 | Bank Of America | 381.92 Bn | -1,994.15 Bn | - |
| 4 | Hsbc Holdings | 341.10 Bn | 341.15 Bn | - |
| 5 | Morgan Stanley | 295.71 Bn | -213.38 Bn | - |
| 6 | Royal Bank Of Canada | 275.38 Bn | 126.13 Bn | - |
| 7 | Mitsubishi Ufj Financial | 273.79 Bn | -1,314.70 Bn | 10.89 Bn |
| 8 | Goldman Sachs | 262.78 Bn | -3,294.34 Bn | - |
| 9 | Wells Fargo & Company | 242.61 Bn | 244.75 Bn | - |
| 10 | Orange County Bancorp | 495.42 Mn | 495.42 Mn | - |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.96 Mn |
| Mar 31, 2026 | 1.88 Mn |
| Dec 31, 2025 | 1.93 Mn |
| Sep 30, 2025 | 1.79 Mn |
| Jun 30, 2025 | 2.12 Mn |
| Mar 31, 2025 | 1.98 Mn |
| Dec 31, 2024 | 2.71 Mn |
| Sep 30, 2024 | 1.56 Mn |
| Jun 30, 2024 | 1.43 Mn |
| Mar 31, 2024 | 1.44 Mn |
| Dec 31, 2023 | 1.34 Mn |
| Sep 30, 2023 | 1.23 Mn |
| Jun 30, 2023 | 1.67 Mn |
| Mar 31, 2023 | 1.28 Mn |
| Dec 31, 2022 | 1.17 Mn |
| Sep 30, 2022 | 1.28 Mn |
| Jun 30, 2022 | 1.24 Mn |
| Mar 31, 2022 | 1.12 Mn |
| Dec 31, 2021 | 1.96 Mn |
| Sep 30, 2021 | 1.12 Mn |
Orange County Bancorp Other 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=other-operating-expenses&ticker=OBT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-operating-expenses", "ticker": "OBT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=other-operating-expenses&ticker=OBT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();