Us Bancorp \De\ (USB) Provision for Credit Losses (2009 - 2026)
Us Bancorp (USB) recorded Provision for Credit Losses of $654 million in Q3 2026, up 14.5% from $571 million a year earlier and up 21.6% from the prior quarter.
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Analysis
Us Bancorp \De\ (USB) Provision for Credit Losses (2009 - 2026) Analysis & Trends
On a TTM basis, Us Bancorp's Provision for Credit Losses came in at $2.35 billion as of Sep 30, 2026, up 8.1% year-over-year; for FY2025, it was $2.19 billion, down 2.3% from FY2024.
- Annual Provision for Credit Losses has a five-year compound annual growth rate of -10.5% (FY2020 to FY2025).
- Across earlier years, Provision for Credit Losses came in at $2.24 billion in FY2024 (-1.6%), $2.28 billion in FY2023 (+15.1%), $1.98 billion in FY2022 and -$1.17 billion in FY2021.
- The Q3 2026 figure is the highest quarterly Provision for Credit Losses since Q2 2023.
- On a year-over-year basis, Provision for Credit Losses has increased for five consecutive quarters, with growth averaging 3.7% over the last eight quarters.
- Peak year-over-year performance for Provision for Credit Losses in the last five years was growth of 281.3% in Q1 2023, against a decline of 57.0% in Q4 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $538 million (Q2 2026), $576 million (Q1 2026) and $577 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Provisions (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 920.14 Bn | 897.90 Bn | - | 2.74 Bn |
| 2 | Banco Santander Chile | 407.42 Bn | -7,109.68 Bn | - | 838.45 Bn |
| 3 | Bank Of America | 353.20 Bn | -2,022.91 Bn | - | 1.24 Bn |
| 4 | Hsbc Holdings | 307.88 Bn | -2,967.28 Bn | - | - |
| 5 | Morgan Stanley | 298.41 Bn | -244.41 Bn | - | 103.00 Mn |
| 6 | Royal Bank Of Canada | 283.46 Bn | -546.54 Bn | - | 717.20 Mn |
| 7 | Goldman Sachs | 264.45 Bn | -3,478.99 Bn | - | 368.00 Mn |
| 8 | Mitsubishi Ufj Financial | 259.19 Bn | -159.36 Bn | 5.24 Bn | - |
| 9 | Wells Fargo & Company | 258.28 Bn | 93.72 Bn | - | 1.03 Bn |
| 10 | Us Bancorp \De\ | 95.04 Bn | 95.50 Bn | - | 654.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 654.00 Mn |
| Jun 30, 2026 | 538.00 Mn |
| Mar 31, 2026 | 576.00 Mn |
| Dec 31, 2025 | 577.00 Mn |
| Sep 30, 2025 | 571.00 Mn |
| Jun 30, 2025 | 501.00 Mn |
| Mar 31, 2025 | 537.00 Mn |
| Dec 31, 2024 | 560.00 Mn |
| Sep 30, 2024 | 557.00 Mn |
| Jun 30, 2024 | 568.00 Mn |
| Mar 31, 2024 | 553.00 Mn |
| Dec 31, 2023 | 512.00 Mn |
| Sep 30, 2023 | 515.00 Mn |
| Jun 30, 2023 | 821.00 Mn |
| Mar 31, 2023 | 427.00 Mn |
| Dec 31, 2022 | 1.19 Bn |
| Sep 30, 2022 | 362.00 Mn |
| Jun 30, 2022 | 311.00 Mn |
| Mar 31, 2022 | 112.00 Mn |
| Dec 31, 2021 | -13.00 Mn |
API Access
Us Bancorp \De\ Provision for Credit 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-credit-losses&ticker=USB&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "provision-for-credit-losses", "ticker": "USB", "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-credit-losses&ticker=USB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();