American Express (AXP) Other Operating Expenses (2009 - 2026)
American Express' Other Operating Expenses was $11.98 billion in Q3 2026, up 8.1% from $11.08 billion a year earlier but down 1.3% from the prior quarter.
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Analysis
American Express (AXP) Other Operating Expenses (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, American Express' Other Operating Expenses was $47.48 billion through Sep 30, 2026, up 9.9% year-over-year; for FY2025, it came in at $44.16 billion, up 11.3% from FY2024.
- Other Operating Expenses has now increased for five consecutive years, with a five-year compound annual growth rate of 15.7% (FY2020 to FY2025).
- In earlier years, Other Operating Expenses was $39.67 billion in FY2024 (+7.2%), $37.01 billion in FY2023 (+9.4%), $33.84 billion in FY2022 (+26.0%) and $26.87 billion in FY2021 (+25.9%).
- Quarterly Other Operating Expenses has moved between $7.4 billion (Q1 2022) and $12.14 billion (Q2 2026) over five years.
- Compared with a year earlier, Other Operating Expenses has increased for 22 straight quarters, with growth averaging 11.3% over the last eight quarters.
- Across the past five years, year-over-year growth in Other Operating Expenses ran from 0.9% in Q2 2024 to 42.5% in Q1 2022.
- Per Business Quant data, AXP's Other Operating Expenses in the three quarters before Q3 2026 was $12.14 billion (Q2 2026), $11.4 billion (Q1 2026) and $11.97 billion (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Jpmorgan Chase | 903.97 Bn | 903.97 Bn | - |
| 2 | Bank Of America | 356.92 Bn | -2,019.15 Bn | - |
| 3 | Hsbc Holdings | 296.96 Bn | -1,806.64 Bn | - |
| 4 | Morgan Stanley | 285.10 Bn | 285.10 Bn | - |
| 5 | Royal Bank Of Canada | 284.66 Bn | -545.38 Bn | - |
| 6 | Goldman Sachs | 266.61 Bn | 266.61 Bn | - |
| 7 | Wells Fargo & Company | 250.94 Bn | 250.94 Bn | - |
| 8 | Mitsubishi Ufj Financial | 245.01 Bn | -96.38 Bn | 10.89 Bn |
| 9 | Toronto Dominion Bank | 214.22 Bn | -461.66 Bn | - |
| 10 | American Express | 214.16 Bn | 13.64 Bn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 3.11 Bn |
| Jun 30, 2026 | 3.49 Bn |
| Mar 31, 2026 | 3.05 Bn |
| Dec 31, 2025 | 3.60 Bn |
| Sep 30, 2025 | 3.39 Bn |
| Jun 30, 2025 | 3.28 Bn |
| Mar 31, 2025 | 3.18 Bn |
| Dec 31, 2024 | 3.71 Bn |
| Sep 30, 2024 | 3.21 Bn |
| Jun 30, 2024 | 2.47 Bn |
| Mar 31, 2024 | 2.87 Bn |
| Dec 31, 2023 | 3.58 Bn |
| Sep 30, 2023 | 3.00 Bn |
| Jun 30, 2023 | 2.93 Bn |
| Mar 31, 2023 | 2.96 Bn |
| Dec 31, 2022 | 3.36 Bn |
| Sep 30, 2022 | 2.77 Bn |
| Jun 30, 2022 | 2.86 Bn |
| Mar 31, 2022 | 2.44 Bn |
| Dec 31, 2021 | 2.85 Bn |
API Access
American Express Other 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=other-operating-expenses&ticker=AXP&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-operating-expenses", "ticker": "AXP", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=other-operating-expenses&ticker=AXP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();