Camden National (CAC) Operating Expenses (2010 - 2026)
Camden National (CAC) posted Operating Expenses of $37.36 million for Q2 2026, down 0.6% from $37.6 million a year earlier but up 4.6% from the prior quarter.
Camden National (CAC) Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Camden National was $145.85 million, up 4.7% year-over-year; for FY2025, it came in at $154.83 million, up 38.3% from FY2024.
- Annual Operating Expenses has increased for eight consecutive years, with a five-year compound annual growth rate of 9.1% (FY2020 to FY2025).
- In prior years, Camden National's Operating Expenses was $111.94 million in FY2024 (+4.3%), $107.36 million in FY2023 (+0.5%), $106.85 million in FY2022 (+3.0%) and $103.72 million in FY2021 (+3.7%).
- Quarterly Operating Expenses has run from a low of $26.17 million in Q1 2023 to a high of $44.45 million in Q1 2025 over five years.
- On a year-over-year basis, Operating Expenses increased in six of the last eight quarters, with growth averaging 18.3%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q1 2025, with growth of 62.5%; the weakest was Q1 2026, with a decline of 19.7%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $35.71 million (Q1 2026), $36.86 million (Q4 2025) and $35.93 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 895.36 Bn | 924.83 Bn | - | 27.32 Bn |
| 2 | Banco Santander Chile | 425.01 Bn | 544.95 Bn | - | -3,218.32 Bn |
| 3 | Bank Of America | 389.22 Bn | -1,986.85 Bn | - | 18.63 Bn |
| 4 | Hsbc Holdings | 347.56 Bn | 347.61 Bn | - | - |
| 5 | Morgan Stanley | 304.44 Bn | -204.66 Bn | - | 13.90 Bn |
| 6 | Royal Bank Of Canada | 281.54 Bn | 132.29 Bn | - | 7.02 Bn |
| 7 | Mitsubishi Ufj Financial | 277.23 Bn | -1,311.26 Bn | 10.89 Bn | 17.50 Bn |
| 8 | Goldman Sachs | 267.12 Bn | -3,289.99 Bn | - | 11.67 Bn |
| 9 | Wells Fargo & Company | 244.76 Bn | 246.90 Bn | - | 13.66 Bn |
| 10 | Camden National | 969.89 Mn | 969.89 Mn | - | 37.36 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 37.36 Mn |
| Mar 31, 2026 | 35.71 Mn |
| Dec 31, 2025 | 36.86 Mn |
| Sep 30, 2025 | 35.93 Mn |
| Jun 30, 2025 | 37.60 Mn |
| Mar 31, 2025 | 44.45 Mn |
| Dec 31, 2024 | 28.36 Mn |
| Sep 30, 2024 | 28.90 Mn |
| Jun 30, 2024 | 27.31 Mn |
| Mar 31, 2024 | 27.36 Mn |
| Dec 31, 2023 | 27.85 Mn |
| Sep 30, 2023 | 26.21 Mn |
| Jun 30, 2023 | 27.14 Mn |
| Mar 31, 2023 | 26.17 Mn |
| Dec 31, 2022 | 26.99 Mn |
| Sep 30, 2022 | 27.09 Mn |
| Jun 30, 2022 | 26.56 Mn |
| Mar 31, 2022 | 26.21 Mn |
| Dec 31, 2021 | 26.97 Mn |
| Sep 30, 2021 | 26.26 Mn |
Camden National 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=CAC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "CAC", "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=CAC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();