Valley National Bancorp (VLY) Operating Expenses (2009 - 2026)
Valley National Bancorp (VLY) posted Operating Expenses of $309.96 million for Q3 2026, up 9.9% from $281.99 million a year earlier but down 0.4% from the prior quarter.
Valley National Bancorp (VLY) Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Sep 30, 2026, Operating Expenses at Valley National Bancorp was $1.23 billion, up 9.7% year-over-year; for FY2025, it came in at $1.14 billion, up 3.3% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 12.1% (FY2020 to FY2025).
- In prior years, Valley National Bancorp's Operating Expenses was $1.11 billion in FY2024 (-4.9%), $1.16 billion in FY2023 (+13.4%), $1.02 billion in FY2022 (+48.2%) and $691.54 million in FY2021 (+7.0%).
- Quarterly Operating Expenses has run from a low of $184.51 million in Q4 2021 to a high of $340.42 million in Q4 2023 over five years.
- On a year-over-year basis, Operating Expenses has increased in each of the last six quarters, with growth averaging 3.3% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q2 2022, with growth of 74.4%; the weakest was Q4 2024, with a decline of 18.2%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $311.12 million (Q2 2026), $309.93 million (Q1 2026) and $299.4 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 918.91 Bn | 918.91 Bn | - | 27.30 Bn |
| 2 | Banco Santander Chile | 870.35 Bn | 846.93 Bn | - | - |
| 3 | Bank Of America | 358.55 Bn | -2,017.56 Bn | - | 19.72 Bn |
| 4 | Hsbc Holdings | 315.74 Bn | -668.95 Bn | - | - |
| 5 | Morgan Stanley | 290.88 Bn | -253.14 Bn | - | 13.71 Bn |
| 6 | Royal Bank Of Canada | 287.92 Bn | 137.98 Bn | - | 7.02 Bn |
| 7 | Goldman Sachs | 270.57 Bn | -3,472.88 Bn | - | 11.31 Bn |
| 8 | Wells Fargo & Company | 258.79 Bn | 258.79 Bn | - | 13.74 Bn |
| 9 | Mitsubishi Ufj Financial | 247.94 Bn | 129.81 Bn | - | - |
| 10 | Valley National Bancorp | 7.86 Bn | 7.51 Bn | - | 309.96 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 309.96 Mn |
| Jun 30, 2026 | 311.12 Mn |
| Mar 31, 2026 | 309.93 Mn |
| Dec 31, 2025 | 299.40 Mn |
| Sep 30, 2025 | 281.99 Mn |
| Jun 30, 2025 | 284.12 Mn |
| Mar 31, 2025 | 276.62 Mn |
| Dec 31, 2024 | 278.58 Mn |
| Sep 30, 2024 | 269.47 Mn |
| Jun 30, 2024 | 277.50 Mn |
| Mar 31, 2024 | 280.31 Mn |
| Dec 31, 2023 | 340.42 Mn |
| Sep 30, 2023 | 267.13 Mn |
| Jun 30, 2023 | 282.97 Mn |
| Mar 31, 2023 | 272.17 Mn |
| Dec 31, 2022 | 266.24 Mn |
| Sep 30, 2022 | 261.64 Mn |
| Jun 30, 2022 | 299.73 Mn |
| Mar 31, 2022 | 197.34 Mn |
| Dec 31, 2021 | 184.51 Mn |
Valley National Bancorp 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=VLY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "VLY", "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=VLY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();