State Street (STT) Operating Expenses (2009 - 2026)
State Street (STT) posted Operating Expenses of $2.66 billion for Q2 2026, up 5.1% from $2.53 billion a year earlier but down 5.4% from the prior quarter.
State Street (STT) Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at State Street was $10.65 billion, up 9.4% year-over-year; for FY2025, it was $10.15 billion, up 6.5% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 3.1% (FY2020 to FY2025).
- In prior years, State Street's Operating Expenses was $9.53 billion in FY2024 (-0.6%), $9.58 billion in FY2023 (+8.9%), $8.8 billion in FY2022 (-1.0%) and $8.89 billion in FY2021 (+2.0%).
- Quarterly Operating Expenses has run from a low of $2.11 billion in Q2 2022 to a high of $2.82 billion in Q4 2023 over five years.
- On a year-over-year basis, Operating Expenses has increased in each of the last five quarters, with growth averaging 4.9% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q4 2023, with growth of 25.1%; the weakest was Q4 2024, with a decline of 13.5%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $2.81 billion (Q1 2026), $2.74 billion (Q4 2025) and $2.43 billion (Q3 2025).
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
| Date | Value |
|---|---|
| Jun 30, 2026 | 2.66 Bn |
| Mar 31, 2026 | 2.81 Bn |
| Dec 31, 2025 | 2.74 Bn |
| Sep 30, 2025 | 2.43 Bn |
| Jun 30, 2025 | 2.53 Bn |
| Mar 31, 2025 | 2.45 Bn |
| Dec 31, 2024 | 2.44 Bn |
| Sep 30, 2024 | 2.31 Bn |
| Jun 30, 2024 | 2.27 Bn |
| Mar 31, 2024 | 2.51 Bn |
| Dec 31, 2023 | 2.82 Bn |
| Sep 30, 2023 | 2.18 Bn |
| Jun 30, 2023 | 2.21 Bn |
| Mar 31, 2023 | 2.37 Bn |
| Dec 31, 2022 | 2.26 Bn |
| Sep 30, 2022 | 2.11 Bn |
| Jun 30, 2022 | 2.11 Bn |
| Mar 31, 2022 | 2.33 Bn |
| Dec 31, 2021 | 2.33 Bn |
| Sep 30, 2021 | 2.12 Bn |
State Street 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=STT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "STT", "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=STT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();