Bank of New York Mellon (BNY) Operating Expenses (2009 - 2026)
Bank of New York Mellon's Operating Expenses came in at $3.44 billion for Q2 2026, up 7.3% from $3.21 billion a year earlier and up 1.1% from the prior quarter.
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Analysis
Bank of New York Mellon (BNY) Operating Expenses (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Bank of New York Mellon reported Operating Expenses of $13.44 billion, up 4.0% year-over-year; for FY2025, it came in at $13.05 billion, up 2.8% from FY2024.
- Operating Expenses carries a five-year compound annual growth rate of 3.5% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $12.7 billion in FY2024 (-4.5%), $13.3 billion in FY2023 (+2.2%), $13.01 billion in FY2022 (+13.0%) and $11.51 billion in FY2021 (+4.6%).
- The Q2 2026 figure represents the highest quarterly Operating Expenses since Q4 2023.
- Year-over-year, Operating Expenses has increased for six consecutive quarters, with growth averaging 0.9% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in Q3 2022 (growth of 26.1%), and the weakest in Q3 2023 (a decline of 16.0%).
- Business Quant data shows BNY's Operating Expenses at $3.4 billion (Q1 2026), $3.36 billion (Q4 2025) and $3.24 billion (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Robinhood Markets | 104.70 Bn | 85.79 Bn | - | 734.00 Mn |
| 2 | Bank of New York Mellon | 100.72 Bn | 40.09 Bn | - | 3.44 Bn |
| 3 | Cme | 94.58 Bn | 94.58 Bn | - | 599.10 Mn |
| 4 | Intercontinental Exchange | 85.83 Bn | 79.63 Bn | - | 1.28 Bn |
| 5 | Nasdaq | 52.05 Bn | 49.49 Bn | 1.50 Bn | 788.00 Mn |
| 6 | State Street | 49.39 Bn | 49.39 Bn | - | 2.66 Bn |
| 7 | Interactive Brokers | 39.24 Bn | 32.69 Bn | - | 440.00 Mn |
| 8 | Northern Trust | 31.94 Bn | 31.94 Bn | - | 1.64 Bn |
| 9 | Cboe Global Markets | 26.47 Bn | 18.13 Bn | 731.60 Mn | 255.60 Mn |
| 10 | LPL Financial Holdings | 24.62 Bn | 19.94 Bn | - | 4.67 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 3.44 Bn |
| Mar 31, 2026 | 3.40 Bn |
| Dec 31, 2025 | 3.36 Bn |
| Sep 30, 2025 | 3.24 Bn |
| Jun 30, 2025 | 3.21 Bn |
| Mar 31, 2025 | 3.25 Bn |
| Dec 31, 2024 | 3.36 Bn |
| Sep 30, 2024 | 3.10 Bn |
| Jun 30, 2024 | 3.07 Bn |
| Mar 31, 2024 | 3.18 Bn |
| Dec 31, 2023 | 4.00 Bn |
| Sep 30, 2023 | 3.09 Bn |
| Jun 30, 2023 | 3.11 Bn |
| Mar 31, 2023 | 3.10 Bn |
| Dec 31, 2022 | 3.21 Bn |
| Sep 30, 2022 | 3.68 Bn |
| Jun 30, 2022 | 3.11 Bn |
| Mar 31, 2022 | 3.01 Bn |
| Dec 31, 2021 | 2.97 Bn |
| Sep 30, 2021 | 2.92 Bn |
API Access
Bank of New York Mellon 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=BNY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "BNY", "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=BNY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();