Provident Financial Services (PFS) Operating Expenses (2009 - 2026)
Provident Financial Services (PFS) recorded Operating Expenses of $119.26 million in Q2 2026, up 4.1% from $114.61 million a year earlier and up 1.8% from the prior quarter.
Provident Financial Services (PFS) Operating Expenses (2009 - 2026) Analysis & Trends
On a TTM basis, Provident Financial Services' Operating Expenses came in at $464.18 million as of Jun 30, 2026, down 7.4% year-over-year; for FY2025, it was $458.66 million, up 0.2% from FY2024.
- Annual Operating Expenses has increased for 12 straight years, with a five-year compound annual growth rate of 15.0% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $457.55 million in FY2024 (+66.2%), $275.34 million in FY2023 (+5.8%), $260.23 million in FY2022 (+4.1%) and $250.05 million in FY2021 (+9.8%).
- The Q2 2026 figure is the highest quarterly Operating Expenses since Q4 2024.
- On a year-over-year basis, Operating Expenses rose in five of the last eight quarters, with growth averaging 27.4%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 107.2% in Q3 2024, against a decline of 16.8% in Q3 2025 at the low end.
- Per Business Quant, the preceding three quarters came in at $117.14 million (Q1 2026), $114.69 million (Q4 2025) and $113.09 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 | Provident Financial Services | 2.94 Bn | 2.20 Bn | - | 119.26 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 119.26 Mn |
| Mar 31, 2026 | 117.14 Mn |
| Dec 31, 2025 | 114.69 Mn |
| Sep 30, 2025 | 113.09 Mn |
| Jun 30, 2025 | 114.61 Mn |
| Mar 31, 2025 | 116.27 Mn |
| Dec 31, 2024 | 134.32 Mn |
| Sep 30, 2024 | 136.00 Mn |
| Jun 30, 2024 | 115.39 Mn |
| Mar 31, 2024 | 71.83 Mn |
| Dec 31, 2023 | 75.85 Mn |
| Sep 30, 2023 | 65.63 Mn |
| Jun 30, 2023 | 65.11 Mn |
| Mar 31, 2023 | 69.49 Mn |
| Dec 31, 2022 | 65.06 Mn |
| Sep 30, 2022 | 69.44 Mn |
| Jun 30, 2022 | 63.85 Mn |
| Mar 31, 2022 | 61.89 Mn |
| Dec 31, 2021 | 62.06 Mn |
| Sep 30, 2021 | 63.44 Mn |
Provident Financial Services 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=PFS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "PFS", "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=PFS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();