American Express (AXP) Provision for Losses (2010 - 2026)
American Express (AXP) reported Provision for Losses of $985 million for Q3 2026, down 23.5% from $1.29 billion a year earlier and down 9.1% from the prior quarter.
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Analysis
American Express (AXP) Provision for Losses (2010 - 2026) Analysis & Trends
Over the twelve months ended Sep 30, 2026, American Express' Provision for Losses came in at $4.73 billion, down 7.8% year-over-year; for FY2025, it was $5.26 billion, up 1.4% from FY2024.
- Provision for Losses has increased for three consecutive years, with a five-year compound annual growth rate of 2.1% (FY2020 to FY2025).
- By year, Provision for Losses came in at $5.19 billion in FY2024 (+5.3%), $4.92 billion in FY2023 (+125.6%), $2.18 billion in FY2022 and -$1.42 billion in FY2021.
- The Q3 2026 figure ranks as the lowest quarterly Provision for Losses since Q3 2022.
- Year over year, Provision for Losses gained in three of the last eight quarters, with an average decline of 5.2%.
- The high point for year-over-year Provision for Losses in five years was Q2 2023 (growth of 192.2%); the low point was Q3 2026 (a decline of 23.5%).
- Per Business Quant data, the three quarters before Q3 2026 came in at $1.08 billion (Q2 2026), $1.25 billion (Q1 2026) and $1.41 billion (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Provision for Losses (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 903.97 Bn | 903.97 Bn | - | - |
| 2 | Bank Of America | 356.92 Bn | -2,019.15 Bn | - | 1.40 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 | - | 717.20 Mn |
| 6 | Goldman Sachs | 266.61 Bn | 266.61 Bn | - | - |
| 7 | Wells Fargo & Company | 250.94 Bn | 250.94 Bn | - | 1.03 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 | - | 985.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 985.00 Mn |
| Jun 30, 2026 | 1.08 Bn |
| Mar 31, 2026 | 1.25 Bn |
| Dec 31, 2025 | 1.41 Bn |
| Sep 30, 2025 | 1.29 Bn |
| Jun 30, 2025 | 1.41 Bn |
| Mar 31, 2025 | 1.15 Bn |
| Dec 31, 2024 | 1.29 Bn |
| Sep 30, 2024 | 1.36 Bn |
| Jun 30, 2024 | 1.27 Bn |
| Mar 31, 2024 | 1.27 Bn |
| Dec 31, 2023 | 1.44 Bn |
| Sep 30, 2023 | 1.23 Bn |
| Jun 30, 2023 | 1.20 Bn |
| Mar 31, 2023 | 1.06 Bn |
| Dec 31, 2022 | 1.03 Bn |
| Sep 30, 2022 | 778.00 Mn |
| Jun 30, 2022 | 410.00 Mn |
| Mar 31, 2022 | -33.00 Mn |
| Dec 31, 2021 | 53.00 Mn |
API Access
American Express Provision for Losses 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=provision-for-losses&ticker=AXP&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "provision-for-losses", "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=provision-for-losses&ticker=AXP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();