Norwood Financial (NWFL) Operating Expenses (2010 - 2026)
Norwood Financial (NWFL) reported Operating Expenses of $15.79 million for Q2 2026, up 26.0% from $12.53 million a year earlier but down 24.8% from the prior quarter.
Norwood Financial (NWFL) Operating Expenses (2010 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Norwood Financial's Operating Expenses came in at $63.34 million, up 26.6% year-over-year; for FY2025, it came in at $51.15 million, up 5.2% from FY2024.
- Operating Expenses has increased for ten consecutive years, with a five-year compound annual growth rate of 8.2% (FY2020 to FY2025).
- By year, Operating Expenses came in at $48.63 million in FY2024 (+11.8%), $43.5 million in FY2023 (+6.0%), $41.04 million in FY2022 (+6.3%) and $38.61 million in FY2021 (+12.1%).
- Five-year quarterly Operating Expenses spans a low of $9.62 million in Q3 2021 and a high of $20.99 million in Q1 2026.
- Year over year, Operating Expenses has now increased in each of the last 33 quarters, with growth averaging 19.0% over the last eight quarters.
- Across the past five years, year-over-year growth in Operating Expenses ran from 1.4% in Q4 2021 to 74.0% in Q1 2026.
- Per Business Quant data, the three quarters before Q2 2026 came in at $20.99 million (Q1 2026), $13.62 million (Q4 2025) and $12.93 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 890.60 Bn | 920.07 Bn | - | 27.32 Bn |
| 2 | Banco Santander Chile | 421.74 Bn | 541.68 Bn | - | -3,218.32 Bn |
| 3 | Bank Of America | 385.85 Bn | -1,990.22 Bn | - | 18.63 Bn |
| 4 | Hsbc Holdings | 345.94 Bn | 345.99 Bn | - | - |
| 5 | Morgan Stanley | 303.15 Bn | -205.95 Bn | - | 13.90 Bn |
| 6 | Royal Bank Of Canada | 279.82 Bn | 130.57 Bn | - | 7.02 Bn |
| 7 | Mitsubishi Ufj Financial | 274.62 Bn | -1,313.87 Bn | 10.89 Bn | 17.50 Bn |
| 8 | Goldman Sachs | 267.07 Bn | -3,290.04 Bn | - | 11.67 Bn |
| 9 | Wells Fargo & Company | 243.79 Bn | 245.93 Bn | - | 13.66 Bn |
| 10 | Norwood Financial | 363.48 Mn | 81.45 Mn | - | 15.79 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 15.79 Mn |
| Mar 31, 2026 | 20.99 Mn |
| Dec 31, 2025 | 13.62 Mn |
| Sep 30, 2025 | 12.93 Mn |
| Jun 30, 2025 | 12.53 Mn |
| Mar 31, 2025 | 12.06 Mn |
| Dec 31, 2024 | 13.42 Mn |
| Sep 30, 2024 | 12.03 Mn |
| Jun 30, 2024 | 11.44 Mn |
| Mar 31, 2024 | 11.73 Mn |
| Dec 31, 2023 | 10.85 Mn |
| Sep 30, 2023 | 11.28 Mn |
| Jun 30, 2023 | 10.94 Mn |
| Mar 31, 2023 | 10.44 Mn |
| Dec 31, 2022 | 10.28 Mn |
| Sep 30, 2022 | 10.14 Mn |
| Jun 30, 2022 | 10.47 Mn |
| Mar 31, 2022 | 10.16 Mn |
| Dec 31, 2021 | 10.05 Mn |
| Sep 30, 2021 | 9.62 Mn |
Norwood Financial 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=NWFL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "NWFL", "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=NWFL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();