Trustmark (TRMK) Operating Expenses (2009 - 2026)
Trustmark (TRMK) recorded Operating Expenses of $133.68 million in Q2 2026, up 6.8% from $125.11 million a year earlier and up 1.2% from the prior quarter.
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Analysis
Trustmark (TRMK) Operating Expenses (2009 - 2026) Analysis & Trends
On a TTM basis, Trustmark's Operating Expenses came in at $528.95 million as of Jun 30, 2026, up 6.5% year-over-year; for FY2025, it was $512.23 million, up 5.5% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 1.9% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $485.69 million in FY2024 (-2.0%), $495.7 million in FY2023 (-12.1%), $564.13 million in FY2022 (+15.3%) and $489.3 million in FY2021 (+4.9%).
- The Q2 2026 figure is the highest quarterly Operating Expenses since Q4 2022.
- On a year-over-year basis, Operating Expenses has increased for six consecutive quarters, with growth averaging 3.6% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 60.8% in Q4 2022, against a decline of 34.3% in Q4 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $132.16 million (Q1 2026), $132.17 million (Q4 2025) and $130.93 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 | Trustmark | 2.61 Bn | 2.61 Bn | - | 133.68 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 133.68 Mn |
| Mar 31, 2026 | 132.16 Mn |
| Dec 31, 2025 | 132.17 Mn |
| Sep 30, 2025 | 130.93 Mn |
| Jun 30, 2025 | 125.11 Mn |
| Mar 31, 2025 | 124.01 Mn |
| Dec 31, 2024 | 124.43 Mn |
| Sep 30, 2024 | 123.27 Mn |
| Jun 30, 2024 | 118.33 Mn |
| Mar 31, 2024 | 119.66 Mn |
| Dec 31, 2023 | 126.20 Mn |
| Sep 30, 2023 | 130.29 Mn |
| Jun 30, 2023 | 121.62 Mn |
| Mar 31, 2023 | 128.33 Mn |
| Dec 31, 2022 | 192.15 Mn |
| Sep 30, 2022 | 126.70 Mn |
| Jun 30, 2022 | 123.77 Mn |
| Mar 31, 2022 | 121.52 Mn |
| Dec 31, 2021 | 119.47 Mn |
| Sep 30, 2021 | 129.60 Mn |
API Access
Trustmark 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=TRMK&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "TRMK", "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=TRMK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();