Bank Of America (BAC) Provision for Losses (2009 - 2026)
Bank Of America's Provision for Losses came in at $1.4 billion for Q2 2026, down 12.1% from $1.59 billion a year earlier but up 4.7% from the prior quarter.
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Analysis
Bank Of America (BAC) Provision for Losses (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Bank Of America reported Provision for Losses of $5.37 billion, down 11.6% year-over-year; for FY2025, it was $5.7 billion, down 2.1% from FY2024.
- Provision for Losses carries a five-year compound annual growth rate of -12.8% (FY2020 to FY2025).
- Going back by year, Provision for Losses was $5.82 billion in FY2024 (+32.3%), $4.4 billion in FY2023 (+73.0%), $2.54 billion in FY2022 and -$4.6 billion in FY2021.
- The five-year range for quarterly Provision for Losses is -$624 million (Q3 2021) to $1.59 billion (Q2 2025).
- Year-over-year, Provision for Losses has declined for four consecutive quarters, with growth averaging 3.5% over the last eight quarters.
- The fastest year-over-year change in Provision for Losses over five years came in Q2 2023 (growth of 115.1%), and the weakest in Q3 2025 (a decline of 16.0%).
- Business Quant data shows BAC's Provision for Losses at $1.34 billion (Q1 2026), $1.33 billion (Q4 2025) and $1.3 billion (Q3 2025) in the three quarters before Q2 2026.
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 |
|---|---|
| Jun 30, 2026 | 1.40 Bn |
| Mar 31, 2026 | 1.34 Bn |
| Dec 31, 2025 | 1.33 Bn |
| Sep 30, 2025 | 1.30 Bn |
| Jun 30, 2025 | 1.59 Bn |
| Mar 31, 2025 | 1.48 Bn |
| Dec 31, 2024 | 1.45 Bn |
| Sep 30, 2024 | 1.54 Bn |
| Jun 30, 2024 | 1.51 Bn |
| Mar 31, 2024 | 1.32 Bn |
| Dec 31, 2023 | 1.11 Bn |
| Sep 30, 2023 | 1.23 Bn |
| Jun 30, 2023 | 1.13 Bn |
| Mar 31, 2023 | 931.00 Mn |
| Dec 31, 2022 | 1.09 Bn |
| Sep 30, 2022 | 898.00 Mn |
| Jun 30, 2022 | 523.00 Mn |
| Mar 31, 2022 | 30.00 Mn |
| Dec 31, 2021 | -495.00 Mn |
| Sep 30, 2021 | -624.00 Mn |
API Access
Bank Of America 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=BAC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "provision-for-losses", "ticker": "BAC", "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=BAC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();