Wsfs Financial (WSFS) EBITDA (2010 - 2026)
Wsfs Financial's EBITDA was $181.82 million in Q2 2026, up 3.3% from $175.98 million a year earlier but down 2.7% from the prior quarter.
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Analysis
Wsfs Financial (WSFS) EBITDA (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Wsfs Financial's EBITDA was $724.54 million through Jun 30, 2026, up 1.9% year-over-year; for FY2025, it came in at $701.58 million, down 4.5% from FY2024.
- EBITDA shows a five-year compound annual growth rate of 26.2% (FY2020 to FY2025).
- In earlier years, EBITDA was $734.96 million in FY2024 (+13.1%), $649.72 million in FY2023 (+69.2%), $384.09 million in FY2022 (-5.5%) and $406.41 million in FY2021 (+85.3%).
- Quarterly EBITDA has moved between $26.31 million (Q1 2022) and $188.58 million (Q3 2024) over five years.
- Compared with a year earlier, EBITDA was higher in three of the last eight quarters, with growth averaging 0.2%.
- The best year-over-year quarter for EBITDA over five years was Q1 2023 (growth of 415.5%); the worst was Q1 2022 (a decline of 73.5%).
- Per Business Quant data, WSFS's EBITDA in the three quarters before Q2 2026 was $186.87 million (Q1 2026), $173.96 million (Q4 2025) and $181.9 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 890.60 Bn | 920.07 Bn | - | 54.95 Bn |
| 2 | Banco Santander Chile | 421.74 Bn | 541.68 Bn | - | -1,174.27 Bn |
| 3 | Bank Of America | 385.85 Bn | -1,990.22 Bn | - | 30.01 Bn |
| 4 | Hsbc Holdings | 345.94 Bn | 345.99 Bn | - | - |
| 5 | Morgan Stanley | 303.15 Bn | -205.95 Bn | - | 21.67 Bn |
| 6 | Royal Bank Of Canada | 279.82 Bn | 130.57 Bn | - | 18.88 Bn |
| 7 | Mitsubishi Ufj Financial | 274.62 Bn | -1,313.87 Bn | 10.89 Bn | - |
| 8 | Goldman Sachs | 267.07 Bn | -3,290.04 Bn | - | 27.17 Bn |
| 9 | Wells Fargo & Company | 243.79 Bn | 245.93 Bn | - | 20.89 Bn |
| 10 | Wsfs Financial | 3.87 Bn | -4.45 Bn | - | 181.82 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 181.82 Mn |
| Mar 31, 2026 | 186.87 Mn |
| Dec 31, 2025 | 173.96 Mn |
| Sep 30, 2025 | 181.90 Mn |
| Jun 30, 2025 | 175.98 Mn |
| Mar 31, 2025 | 169.75 Mn |
| Dec 31, 2024 | 176.58 Mn |
| Sep 30, 2024 | 188.58 Mn |
| Jun 30, 2024 | 188.51 Mn |
| Mar 31, 2024 | 181.30 Mn |
| Dec 31, 2023 | 179.86 Mn |
| Sep 30, 2023 | 174.14 Mn |
| Jun 30, 2023 | 160.10 Mn |
| Mar 31, 2023 | 135.63 Mn |
| Dec 31, 2022 | 139.71 Mn |
| Sep 30, 2022 | 117.68 Mn |
| Jun 30, 2022 | 100.39 Mn |
| Mar 31, 2022 | 26.31 Mn |
| Dec 31, 2021 | 84.55 Mn |
| Sep 30, 2021 | 82.89 Mn |
API Access
Wsfs Financial EBITDA 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=ebitda&ticker=WSFS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "WSFS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=ebitda&ticker=WSFS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();