Hancock Whitney (HWC) Provision for Losses (2009 - 2026)
Hancock Whitney's Provision for Losses came in at $13.78 million for Q2 2026, down 7.7% from $14.93 million a year earlier but up 4.6% from the prior quarter.
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Analysis
Hancock Whitney (HWC) Provision for Losses (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Hancock Whitney reported Provision for Losses of $52.74 million, down 5.6% year-over-year; for FY2025, it came in at $51.18 million, down 1.9% from FY2024.
- Provision for Losses carries a five-year compound annual growth rate of -38.9% (FY2020 to FY2025).
- Going back by year, Provision for Losses was $52.17 million in FY2024 (-11.7%), $59.1 million in FY2023, -$28.4 million in FY2022 and -$77.49 million in FY2021.
- The five-year range for quarterly Provision for Losses is -$28.4 million (Q4 2021) to $28.5 million (Q3 2023).
- Year-over-year, Provision for Losses increased in three of the last eight quarters, with an average decline of 2.0%.
- The fastest year-over-year change in Provision for Losses over five years came in Q4 2023 (growth of 581.6%), and the weakest in Q3 2024 (a decline of 34.9%).
- Business Quant data shows HWC's Provision for Losses at $13.17 million (Q1 2026), $13.15 million (Q4 2025) and $12.65 million (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 | 920.14 Bn | 897.90 Bn | - | 2.74 Bn |
| 2 | Banco Santander Chile | 407.42 Bn | -7,109.68 Bn | - | - |
| 3 | Bank Of America | 353.20 Bn | -2,022.91 Bn | - | 1.30 Bn |
| 4 | Hsbc Holdings | 307.88 Bn | -2,967.28 Bn | - | - |
| 5 | Morgan Stanley | 298.41 Bn | -244.41 Bn | - | - |
| 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 | Hancock Whitney | 5.19 Bn | 2.93 Bn | - | 16.10 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 16.10 Mn |
| Jun 30, 2026 | 13.78 Mn |
| Mar 31, 2026 | 13.17 Mn |
| Dec 31, 2025 | 13.15 Mn |
| Sep 30, 2025 | 12.65 Mn |
| Jun 30, 2025 | 14.93 Mn |
| Mar 31, 2025 | 10.46 Mn |
| Dec 31, 2024 | 11.91 Mn |
| Sep 30, 2024 | 18.56 Mn |
| Jun 30, 2024 | 8.72 Mn |
| Mar 31, 2024 | 12.97 Mn |
| Dec 31, 2023 | 16.95 Mn |
| Sep 30, 2023 | 28.50 Mn |
| Jun 30, 2023 | 7.63 Mn |
| Mar 31, 2023 | 6.02 Mn |
| Dec 31, 2022 | 2.49 Mn |
| Sep 30, 2022 | 1.40 Mn |
| Jun 30, 2022 | -9.76 Mn |
| Mar 31, 2022 | -22.53 Mn |
| Dec 31, 2021 | -28.40 Mn |
API Access
Hancock Whitney 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=HWC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "provision-for-losses", "ticker": "HWC", "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=HWC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();