ConnectOne Bancorp (CNOB) Provision for Losses (2009 - 2026)
ConnectOne Bancorp (CNOB) posted Provision for Losses of $8.3 million for Q2 2026, down 76.8% from $35.7 million a year earlier but up 59.6% from the prior quarter.
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Analysis
ConnectOne Bancorp (CNOB) Provision for Losses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Provision for Losses at ConnectOne Bancorp was $21.3 million, down 54.2% year-over-year; for FY2025, it was $47 million, up 240.6% from FY2024.
- Annual Provision for Losses shows a five-year compound annual growth rate of 2.8% (FY2020 to FY2025).
- In prior years, ConnectOne Bancorp's Provision for Losses was $13.8 million in FY2024 (+68.3%), $8.2 million in FY2023 (-53.8%), $17.75 million in FY2022 and -$5.5 million in FY2021.
- Quarterly Provision for Losses has run from a low of $815,000 in Q4 2021 to a high of $35.7 million in Q2 2025 over five years.
- On a year-over-year basis, Provision for Losses increased in four of the last seven quarters, with growth averaging 21.8%.
- The strongest year-over-year quarter for Provision for Losses in the past five years was Q3 2022, with growth of 809.1%; the weakest was Q3 2023, with a decline of 85.0%.
- According to Business Quant data, Provision for Losses for the three prior quarters was $5.2 million (Q1 2026), $2.3 million (Q4 2025) and $5.5 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Provision for Losses (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 909.02 Bn | 886.77 Bn | - | 2.74 Bn |
| 2 | Banco Santander Chile | 406.67 Bn | -7,110.43 Bn | - | - |
| 3 | Bank Of America | 350.91 Bn | -2,025.20 Bn | - | 1.30 Bn |
| 4 | Hsbc Holdings | 308.71 Bn | -2,966.46 Bn | - | - |
| 5 | Morgan Stanley | 293.66 Bn | -249.15 Bn | - | - |
| 6 | Royal Bank Of Canada | 283.56 Bn | -546.44 Bn | - | 717.20 Mn |
| 7 | Goldman Sachs | 262.71 Bn | -3,480.74 Bn | - | 368.00 Mn |
| 8 | Wells Fargo & Company | 257.44 Bn | 92.87 Bn | - | 1.03 Bn |
| 9 | Mitsubishi Ufj Financial | 256.82 Bn | -75.42 Bn | 10.89 Bn | - |
| 10 | ConnectOne Bancorp | 1.65 Bn | -2.17 Bn | - | 5.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 5.00 Mn |
| Jun 30, 2026 | 8.30 Mn |
| Mar 31, 2026 | 5.20 Mn |
| Dec 31, 2025 | 2.30 Mn |
| Sep 30, 2025 | 5.50 Mn |
| Jun 30, 2025 | 35.70 Mn |
| Mar 31, 2025 | 3.50 Mn |
| Dec 31, 2024 | 3.50 Mn |
| Sep 30, 2024 | 3.80 Mn |
| Jun 30, 2024 | 2.50 Mn |
| Mar 31, 2024 | 4.00 Mn |
| Dec 31, 2023 | 2.70 Mn |
| Sep 30, 2023 | 1.50 Mn |
| Jun 30, 2023 | 3.00 Mn |
| Mar 31, 2023 | 1.00 Mn |
| Dec 31, 2022 | 3.30 Mn |
| Sep 30, 2022 | 10.00 Mn |
| Jun 30, 2022 | 3.00 Mn |
| Mar 31, 2022 | 1.45 Mn |
| Dec 31, 2021 | 815,000.00 |
API Access
ConnectOne Bancorp 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=CNOB&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "provision-for-losses", "ticker": "CNOB", "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=CNOB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();