Hancock Whitney (HWC) Operating Expenses (2009 - 2026)
Hancock Whitney (HWC) posted Operating Expenses of $225.44 million for Q2 2026, up 4.4% from $215.98 million a year earlier and up 2.1% from the prior quarter.
Hancock Whitney (HWC) Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Hancock Whitney was $876.79 million, up 6.0% year-over-year; for FY2025, it came in at $851.64 million, up 3.9% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 1.5% (FY2020 to FY2025).
- In prior years, Hancock Whitney's Operating Expenses was $819.91 million in FY2024 (-2.0%), $836.85 million in FY2023 (+11.5%), $750.69 million in FY2022 (-7.0%) and $807.01 million in FY2021 (+2.3%).
- The Q2 2026 figure stands as the highest quarterly Operating Expenses since Q4 2023.
- On a year-over-year basis, Operating Expenses has increased in each of the last five quarters, with growth averaging 1.9% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q4 2023, with growth of 20.5%; the weakest was Q2 2022, with a decline of 21.0%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $220.75 million (Q1 2026), $217.85 million (Q4 2025) and $212.75 million (Q3 2025).
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 | Hancock Whitney | 5.80 Bn | 3.59 Bn | - | 225.44 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 225.44 Mn |
| Mar 31, 2026 | 220.75 Mn |
| Dec 31, 2025 | 217.85 Mn |
| Sep 30, 2025 | 212.75 Mn |
| Jun 30, 2025 | 215.98 Mn |
| Mar 31, 2025 | 205.06 Mn |
| Dec 31, 2024 | 202.33 Mn |
| Sep 30, 2024 | 203.84 Mn |
| Jun 30, 2024 | 206.02 Mn |
| Mar 31, 2024 | 207.72 Mn |
| Dec 31, 2023 | 229.15 Mn |
| Sep 30, 2023 | 204.68 Mn |
| Jun 30, 2023 | 202.14 Mn |
| Mar 31, 2023 | 200.88 Mn |
| Dec 31, 2022 | 190.15 Mn |
| Sep 30, 2022 | 193.50 Mn |
| Jun 30, 2022 | 187.10 Mn |
| Mar 31, 2022 | 179.94 Mn |
| Dec 31, 2021 | 182.46 Mn |
| Sep 30, 2021 | 194.70 Mn |
Hancock Whitney 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=HWC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "HWC", "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=HWC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();