German American Bancorp (GABC) Operating Expenses (2010 - 2026)
German American Bancorp (GABC) posted Operating Expenses of $50.38 million for Q2 2026, up 1.7% from $49.52 million a year earlier but down 3.8% from the prior quarter.
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Analysis
German American Bancorp (GABC) Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at German American Bancorp was $202.4 million, up 16.1% year-over-year; for FY2025, it was $201.95 million, up 38.0% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 11.5% (FY2020 to FY2025).
- In prior years, German American Bancorp's Operating Expenses was $146.38 million in FY2024 (+1.3%), $144.5 million in FY2023 (-6.3%), $154.19 million in FY2022 (+24.3%) and $124.01 million in FY2021 (+5.9%).
- Quarterly Operating Expenses has run from a low of $31.27 million in Q4 2021 to a high of $52.78 million in Q1 2025 over five years.
- On a year-over-year basis, Operating Expenses increased in seven of the last eight quarters, with growth averaging 19.4%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q1 2022, with growth of 54.1%; the weakest was Q1 2023, with a decline of 21.9%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $52.37 million (Q1 2026), $49.95 million (Q4 2025) and $49.7 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 879.54 Bn | 909.01 Bn | - | 27.32 Bn |
| 2 | Banco Santander Chile | 418.48 Bn | 538.42 Bn | - | -3,218.32 Bn |
| 3 | Bank Of America | 381.92 Bn | -1,994.15 Bn | - | 18.63 Bn |
| 4 | Hsbc Holdings | 341.10 Bn | 341.15 Bn | - | - |
| 5 | Morgan Stanley | 295.71 Bn | -213.38 Bn | - | 13.90 Bn |
| 6 | Royal Bank Of Canada | 275.38 Bn | 126.13 Bn | - | 7.02 Bn |
| 7 | Mitsubishi Ufj Financial | 273.79 Bn | -1,314.70 Bn | 10.89 Bn | 17.50 Bn |
| 8 | Goldman Sachs | 262.78 Bn | -3,294.34 Bn | - | 11.67 Bn |
| 9 | Wells Fargo & Company | 242.61 Bn | 244.75 Bn | - | 13.66 Bn |
| 10 | German American Bancorp | 1.82 Bn | 1.82 Bn | - | 50.38 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 50.38 Mn |
| Mar 31, 2026 | 52.37 Mn |
| Dec 31, 2025 | 49.95 Mn |
| Sep 30, 2025 | 49.70 Mn |
| Jun 30, 2025 | 49.52 Mn |
| Mar 31, 2025 | 52.78 Mn |
| Dec 31, 2024 | 35.84 Mn |
| Sep 30, 2024 | 36.13 Mn |
| Jun 30, 2024 | 37.67 Mn |
| Mar 31, 2024 | 36.74 Mn |
| Dec 31, 2023 | 35.73 Mn |
| Sep 30, 2023 | 35.42 Mn |
| Jun 30, 2023 | 35.73 Mn |
| Mar 31, 2023 | 37.62 Mn |
| Dec 31, 2022 | 35.61 Mn |
| Sep 30, 2022 | 34.72 Mn |
| Jun 30, 2022 | 35.70 Mn |
| Mar 31, 2022 | 48.16 Mn |
| Dec 31, 2021 | 31.27 Mn |
| Sep 30, 2021 | 32.44 Mn |
API Access
German American 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=GABC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "GABC", "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=GABC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();