Wintrust Financial (WTFC) Operating Expenses (2009 - 2026)
Wintrust Financial's Operating Expenses was $397.54 million in Q2 2026, up 4.2% from $381.46 million a year earlier and up 3.9% from the prior quarter.
Wintrust Financial (WTFC) Operating Expenses (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Wintrust Financial's Operating Expenses was $1.54 billion through Jun 30, 2026, up 4.6% year-over-year; for FY2025, it came in at $1.51 billion, up 7.8% from FY2024.
- Operating Expenses has now increased for 16 consecutive years, with a five-year compound annual growth rate of 7.8% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $1.4 billion in FY2024 (+6.9%), $1.31 billion in FY2023 (+11.5%), $1.18 billion in FY2022 (+3.9%) and $1.13 billion in FY2021 (+8.9%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses in data going back to Q2 2009.
- Compared with a year earlier, Operating Expenses has increased for 17 straight quarters, with growth averaging 6.4% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q4 2023 (growth of 17.8%); the worst was Q1 2022 (a decline of 0.9%).
- Per Business Quant data, WTFC's Operating Expenses in the three quarters before Q2 2026 was $382.63 million (Q1 2026), $384.45 million (Q4 2025) and $380.03 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 895.36 Bn | 924.83 Bn | - | 27.32 Bn |
| 2 | Banco Santander Chile | 425.01 Bn | 544.95 Bn | - | -3,218.32 Bn |
| 3 | Bank Of America | 389.22 Bn | -1,986.85 Bn | - | 18.63 Bn |
| 4 | Hsbc Holdings | 347.56 Bn | 347.61 Bn | - | - |
| 5 | Morgan Stanley | 304.44 Bn | -204.66 Bn | - | 13.90 Bn |
| 6 | Royal Bank Of Canada | 281.54 Bn | 132.29 Bn | - | 7.02 Bn |
| 7 | Mitsubishi Ufj Financial | 277.23 Bn | -1,311.26 Bn | 10.89 Bn | 17.50 Bn |
| 8 | Goldman Sachs | 267.12 Bn | -3,289.99 Bn | - | 11.67 Bn |
| 9 | Wells Fargo & Company | 244.76 Bn | 246.90 Bn | - | 13.66 Bn |
| 10 | Wintrust Financial | 9.72 Bn | 5.11 Bn | - | 397.54 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 397.54 Mn |
| Mar 31, 2026 | 382.63 Mn |
| Dec 31, 2025 | 384.45 Mn |
| Sep 30, 2025 | 380.03 Mn |
| Jun 30, 2025 | 381.46 Mn |
| Mar 31, 2025 | 366.09 Mn |
| Dec 31, 2024 | 368.54 Mn |
| Sep 30, 2024 | 360.69 Mn |
| Jun 30, 2024 | 340.35 Mn |
| Mar 31, 2024 | 333.15 Mn |
| Dec 31, 2023 | 362.65 Mn |
| Sep 30, 2023 | 330.06 Mn |
| Jun 30, 2023 | 320.62 Mn |
| Mar 31, 2023 | 299.17 Mn |
| Dec 31, 2022 | 307.84 Mn |
| Sep 30, 2022 | 296.47 Mn |
| Jun 30, 2022 | 288.67 Mn |
| Mar 31, 2022 | 284.30 Mn |
| Dec 31, 2021 | 283.40 Mn |
| Sep 30, 2021 | 282.14 Mn |
Wintrust Financial 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=WTFC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "WTFC", "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=WTFC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();