Great Southern Bancorp (GSBC) Operating Expenses (2010 - 2026)
Great Southern Bancorp (GSBC) recorded Operating Expenses of $38.22 million in Q2 2026, up 9.2% from $35.01 million a year earlier and up 9.9% from the prior quarter.
Great Southern Bancorp (GSBC) Operating Expenses (2010 - 2026) Analysis & Trends
On a TTM basis, Great Southern Bancorp's Operating Expenses came in at $145.13 million as of Jun 30, 2026, up 3.3% year-over-year; for FY2025, it was $141.94 million, up 0.3% from FY2024.
- Annual Operating Expenses has increased for six straight years, with a five-year compound annual growth rate of 2.9% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $141.5 million in FY2024 (+0.3%), $141.02 million in FY2023 (+5.7%), $133.37 million in FY2022 (+4.5%) and $127.64 million in FY2021 (+3.6%).
- The Q2 2026 figure is the highest quarterly Operating Expenses since Q4 2019.
- On a year-over-year basis, Operating Expenses rose in four of the last eight quarters, with growth averaging 1.0%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 15.2% in Q4 2021, against a decline of 5.2% in Q3 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $34.79 million (Q1 2026), $36 million (Q4 2025) and $36.12 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 | Great Southern Bancorp | 844.09 Mn | 90.91 Mn | - | 38.22 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 38.22 Mn |
| Mar 31, 2026 | 34.79 Mn |
| Dec 31, 2025 | 36.00 Mn |
| Sep 30, 2025 | 36.12 Mn |
| Jun 30, 2025 | 35.01 Mn |
| Mar 31, 2025 | 34.82 Mn |
| Dec 31, 2024 | 36.95 Mn |
| Sep 30, 2024 | 33.72 Mn |
| Jun 30, 2024 | 36.41 Mn |
| Mar 31, 2024 | 34.42 Mn |
| Dec 31, 2023 | 36.29 Mn |
| Sep 30, 2023 | 35.56 Mn |
| Jun 30, 2023 | 34.72 Mn |
| Mar 31, 2023 | 34.46 Mn |
| Dec 31, 2022 | 34.34 Mn |
| Sep 30, 2022 | 34.76 Mn |
| Jun 30, 2022 | 33.00 Mn |
| Mar 31, 2022 | 31.27 Mn |
| Dec 31, 2021 | 35.78 Mn |
| Sep 30, 2021 | 31.34 Mn |
Great Southern 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=GSBC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "GSBC", "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=GSBC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();