Regions Financial (RF) Provision for Losses (2010 - 2026)
Regions Financial (RF) reported Provision for Losses of $68 million for Q2 2026, down 46.0% from $126 million a year earlier and down 25.3% from the prior quarter.
Powered by 
Analysis
Regions Financial (RF) Provision for Losses (2010 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Regions Financial's Provision for Losses came in at $379 million, down 21.5% year-over-year; for FY2025, it was $470 million, down 3.5% from FY2024.
- Provision for Losses has a five-year compound annual growth rate of -18.8% (FY2020 to FY2025).
- By year, Provision for Losses came in at $487 million in FY2024 (-11.9%), $553 million in FY2023 (+104.1%), $271 million in FY2022 and -$524 million in FY2021.
- The Q2 2026 figure ranks as the lowest quarterly Provision for Losses since Q2 2022.
- Year over year, Provision for Losses has now declined in each of the last four quarters, with an average decline of 15.4% over the last eight quarters.
- The high point for year-over-year Provision for Losses in five years was Q2 2023 (growth of 96.7%); the low point was Q2 2026 (a decline of 46.0%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $91 million (Q1 2026), $115 million (Q4 2025) and $105 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Provision for Losses (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 905.34 Bn | 905.34 Bn | - | 2.74 Bn |
| 2 | Bank Of America | 358.56 Bn | -2,017.55 Bn | - | 1.30 Bn |
| 3 | Hsbc Holdings | 307.13 Bn | -1,796.46 Bn | - | - |
| 4 | Royal Bank Of Canada | 287.97 Bn | -542.07 Bn | - | 717.20 Mn |
| 5 | Morgan Stanley | 284.27 Bn | -224.82 Bn | - | - |
| 6 | Goldman Sachs | 257.96 Bn | -3,485.49 Bn | - | 368.00 Mn |
| 7 | Wells Fargo & Company | 256.22 Bn | 256.22 Bn | - | 1.03 Bn |
| 8 | Mitsubishi Ufj Financial | 241.27 Bn | -100.12 Bn | 10.89 Bn | - |
| 9 | American Express | 219.29 Bn | 18.77 Bn | - | 985.00 Mn |
| 10 | Regions Financial | 24.32 Bn | 24.32 Bn | - | 68.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 68.00 Mn |
| Mar 31, 2026 | 91.00 Mn |
| Dec 31, 2025 | 115.00 Mn |
| Sep 30, 2025 | 105.00 Mn |
| Jun 30, 2025 | 126.00 Mn |
| Mar 31, 2025 | 124.00 Mn |
| Dec 31, 2024 | 120.00 Mn |
| Sep 30, 2024 | 113.00 Mn |
| Jun 30, 2024 | 102.00 Mn |
| Mar 31, 2024 | 152.00 Mn |
| Dec 31, 2023 | 155.00 Mn |
| Sep 30, 2023 | 145.00 Mn |
| Jun 30, 2023 | 118.00 Mn |
| Mar 31, 2023 | 135.00 Mn |
| Dec 31, 2022 | 112.00 Mn |
| Sep 30, 2022 | 135.00 Mn |
| Jun 30, 2022 | 60.00 Mn |
| Mar 31, 2022 | -36.00 Mn |
| Dec 31, 2021 | 110.00 Mn |
| Sep 30, 2021 | -155.00 Mn |
API Access
Regions Financial 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=RF&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "provision-for-losses", "ticker": "RF", "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=RF&period=max&api_key=YOUR_API_KEY");
const data = await res.json();