Peoples Bancorp (PEBO) Operating Expenses (2009 - 2026)
Peoples Bancorp (PEBO) reported Operating Expenses of $74.54 million for Q3 2026, up 6.6% from $69.89 million a year earlier and up 2.4% from the prior quarter.
Peoples Bancorp (PEBO) Operating Expenses (2009 - 2026) Analysis & Trends
Over the twelve months ended Sep 30, 2026, Peoples Bancorp's Operating Expenses came in at $290.23 million, up 3.1% year-over-year; for FY2025, it came in at $282.34 million, up 3.1% from FY2024.
- Operating Expenses has increased for five consecutive years, with a five-year compound annual growth rate of 16.1% (FY2020 to FY2025).
- By year, Operating Expenses came in at $273.82 million in FY2024 (+2.8%), $266.49 million in FY2023 (+28.6%), $207.15 million in FY2022 (+12.7%) and $183.74 million in FY2021 (+37.4%).
- The Q3 2026 figure ranks as the highest quarterly Operating Expenses in data going back to Q1 2010.
- Year over year, Operating Expenses has now increased in each of the last eight quarters, with growth averaging 3.5% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q4 2021 (growth of 44.3%); the low point was Q3 2022 (a decline of 9.7%).
- Per Business Quant data, the three quarters before Q3 2026 came in at $72.76 million (Q2 2026), $71.64 million (Q1 2026) and $71.29 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 909.02 Bn | 886.77 Bn | - | 27.30 Bn |
| 2 | Banco Santander Chile | 406.67 Bn | -7,110.43 Bn | - | - |
| 3 | Bank Of America | 350.91 Bn | -2,025.20 Bn | - | 19.72 Bn |
| 4 | Hsbc Holdings | 308.71 Bn | -2,966.46 Bn | - | 8.82 Bn |
| 5 | Morgan Stanley | 293.66 Bn | -249.15 Bn | - | 13.71 Bn |
| 6 | Royal Bank Of Canada | 283.56 Bn | -546.44 Bn | - | 7.02 Bn |
| 7 | Goldman Sachs | 262.71 Bn | -3,480.74 Bn | - | 11.31 Bn |
| 8 | Wells Fargo & Company | 257.44 Bn | 92.87 Bn | - | 13.74 Bn |
| 9 | Mitsubishi Ufj Financial | 256.82 Bn | -75.42 Bn | 10.89 Bn | 17.50 Bn |
| 10 | Peoples Bancorp | 1.39 Bn | 444.61 Mn | - | 74.54 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 74.54 Mn |
| Jun 30, 2026 | 72.76 Mn |
| Mar 31, 2026 | 71.64 Mn |
| Dec 31, 2025 | 71.29 Mn |
| Sep 30, 2025 | 69.89 Mn |
| Jun 30, 2025 | 70.36 Mn |
| Mar 31, 2025 | 70.79 Mn |
| Dec 31, 2024 | 70.50 Mn |
| Sep 30, 2024 | 66.09 Mn |
| Jun 30, 2024 | 68.76 Mn |
| Mar 31, 2024 | 68.47 Mn |
| Dec 31, 2023 | 67.69 Mn |
| Sep 30, 2023 | 71.70 Mn |
| Jun 30, 2023 | 70.62 Mn |
| Mar 31, 2023 | 56.48 Mn |
| Dec 31, 2022 | 53.37 Mn |
| Sep 30, 2022 | 52.25 Mn |
| Jun 30, 2022 | 49.90 Mn |
| Mar 31, 2022 | 51.63 Mn |
| Dec 31, 2021 | 47.99 Mn |
Peoples Bancorp 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=PEBO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "PEBO", "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=PEBO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();