Hancock Whitney (HWC) Operating Expenses (2009 - 2026)
Hancock Whitney (HWC) posted Operating Expenses of $262 million for Q3 2026, up 23.1% from $212.75 million a year earlier and up 16.2% from the prior quarter.
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Analysis
Hancock Whitney (HWC) Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Sep 30, 2026, Operating Expenses at Hancock Whitney was $926.04 million, up 10.8% 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 Q3 2026 figure stands as the highest quarterly Operating Expenses in data going back to Q2 2009.
- On a year-over-year basis, Operating Expenses has increased in each of the last six quarters, with growth averaging 4.9% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q3 2026, with growth of 23.1%; the weakest was Q2 2022, with a decline of 21.0%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $225.44 million (Q2 2026), $220.75 million (Q1 2026) and $217.85 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 920.14 Bn | 897.90 Bn | - | 27.30 Bn |
| 2 | Banco Santander Chile | 407.42 Bn | -7,109.68 Bn | - | - |
| 3 | Bank Of America | 353.20 Bn | -2,022.91 Bn | - | 19.72 Bn |
| 4 | Hsbc Holdings | 307.88 Bn | -2,967.28 Bn | - | 8.82 Bn |
| 5 | Morgan Stanley | 298.41 Bn | -244.41 Bn | - | 13.71 Bn |
| 6 | Royal Bank Of Canada | 283.46 Bn | -546.54 Bn | - | 7.02 Bn |
| 7 | Goldman Sachs | 264.45 Bn | -3,478.99 Bn | - | 11.31 Bn |
| 8 | Mitsubishi Ufj Financial | 259.19 Bn | -159.36 Bn | 5.24 Bn | 2.13 Bn |
| 9 | Wells Fargo & Company | 258.28 Bn | 93.72 Bn | - | 13.74 Bn |
| 10 | Hancock Whitney | 5.19 Bn | 2.93 Bn | - | 262.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 262.00 Mn |
| 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 |
API Access
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_KEYimport 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();