Jpmorgan Chase (JPM) Operating Expenses (2009 - 2026)
Jpmorgan Chase (JPM) reported Operating Expenses of $27.32 billion for Q2 2026, up 14.9% from $23.78 billion a year earlier and up 1.7% from the prior quarter.
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Analysis
Jpmorgan Chase (JPM) Operating Expenses (2009 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Jpmorgan Chase's Operating Expenses came in at $102.43 billion, up 10.5% year-over-year; for FY2025, it was $95.64 billion, up 4.2% from FY2024.
- Operating Expenses has increased for nine consecutive years, with a five-year compound annual growth rate of 7.5% (FY2020 to FY2025).
- By year, Operating Expenses came in at $91.8 billion in FY2024 (+5.3%), $87.17 billion in FY2023 (+14.5%), $76.14 billion in FY2022 (+6.7%) and $71.34 billion in FY2021 (+7.0%).
- The Q2 2026 figure ranks as the highest quarterly Operating Expenses in data going back to Q1 2009.
- Year over year, Operating Expenses has now increased in each of the last six quarters, with growth averaging 5.3% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q4 2023 (growth of 28.7%); the low point was Q4 2024 (a decline of 7.0%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $26.85 billion (Q1 2026), $23.98 billion (Q4 2025) and $24.28 billion (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 890.60 Bn | 920.07 Bn | - | 27.32 Bn |
| 2 | Banco Santander Chile | 421.74 Bn | 541.68 Bn | - | -3,218.32 Bn |
| 3 | Bank Of America | 385.85 Bn | -1,990.22 Bn | - | 18.63 Bn |
| 4 | Hsbc Holdings | 345.94 Bn | 345.99 Bn | - | - |
| 5 | Morgan Stanley | 303.15 Bn | -205.95 Bn | - | 13.90 Bn |
| 6 | Royal Bank Of Canada | 279.82 Bn | 130.57 Bn | - | 7.02 Bn |
| 7 | Mitsubishi Ufj Financial | 274.62 Bn | -1,313.87 Bn | 10.89 Bn | 17.50 Bn |
| 8 | Goldman Sachs | 267.07 Bn | -3,290.04 Bn | - | 11.67 Bn |
| 9 | Wells Fargo & Company | 243.79 Bn | 245.93 Bn | - | 13.66 Bn |
| 10 | Banco Santander | 208.29 Bn | 215.91 Bn | - | -7.44 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 27.32 Bn |
| Mar 31, 2026 | 26.85 Bn |
| Dec 31, 2025 | 23.98 Bn |
| Sep 30, 2025 | 24.28 Bn |
| Jun 30, 2025 | 23.78 Bn |
| Mar 31, 2025 | 23.60 Bn |
| Dec 31, 2024 | 22.76 Bn |
| Sep 30, 2024 | 22.57 Bn |
| Jun 30, 2024 | 23.71 Bn |
| Mar 31, 2024 | 22.76 Bn |
| Dec 31, 2023 | 24.49 Bn |
| Sep 30, 2023 | 21.76 Bn |
| Jun 30, 2023 | 20.82 Bn |
| Mar 31, 2023 | 20.11 Bn |
| Dec 31, 2022 | 19.02 Bn |
| Sep 30, 2022 | 19.18 Bn |
| Jun 30, 2022 | 18.75 Bn |
| Mar 31, 2022 | 19.19 Bn |
| Dec 31, 2021 | 17.89 Bn |
| Sep 30, 2021 | 17.06 Bn |
API Access
Jpmorgan Chase 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=JPM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "JPM", "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=JPM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();