Magyar Bancorp (MGYR) Provision for Losses (2009 - 2026)
Magyar Bancorp's Provision for Losses was $351,000 in fiscal Q3 2026 (quarter ended Jun 30, 2026), up 192.5% from $120,000 a year earlier and up 37.1% from the prior quarter.
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Analysis
Magyar Bancorp (MGYR) Provision for Losses (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Magyar Bancorp's Provision for Losses was $932,000 through Jun 30, 2026, up 565.7% year-over-year; for FY2025 (ended Sep 30, 2025), it came in at $653,000, up 258.8% from FY2024.
- Provision for Losses shows a five-year compound annual growth rate of -17.1% (FY2020 to FY2025).
- In earlier fiscal years, Provision for Losses was $182,000 in FY2024 (-52.2%), $381,000 in FY2023 (+25.3%), $304,000 in FY2022 (-81.3%) and $1.63 million in FY2021 (-2.2%).
- The fiscal Q3 2026 figure marks the highest quarterly Provision for Losses since fiscal Q1 2024.
- Compared with a year earlier, Provision for Losses was higher in two of the last four quarters, with growth averaging 83.9%.
- The best year-over-year quarter for Provision for Losses over five years was fiscal Q2 2026 (growth of 265.7%); the worst was fiscal Q2 2022 (a decline of 84.8%).
- Per Business Quant data, MGYR's Provision for Losses in the three fiscal quarters before Q3 2026 was $256,000 (Q2 2026), $71,000 (Q1 2026) and $254,000 (Q4 2025).
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 | Magyar Bancorp | 142.06 Mn | 142.06 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 351,000.00 |
| Mar 31, 2026 | 256,000.00 |
| Dec 31, 2025 | 71,000.00 |
| Sep 30, 2025 | 254,000.00 |
| Jun 30, 2025 | 120,000.00 |
| Mar 31, 2025 | 70,000.00 |
| Dec 31, 2024 | 209,000.00 |
| Sep 30, 2024 | -259,000.00 |
| Jun 30, 2024 | -54,000.00 |
| Mar 31, 2024 | -74,000.00 |
| Dec 31, 2023 | 481,000.00 |
| Sep 30, 2023 | -51,000.00 |
| Jun 30, 2023 | -81,000.00 |
| Mar 31, 2023 | 195,000.00 |
| Dec 31, 2022 | 317,000.00 |
| Sep 30, 2022 | -72,000.00 |
| Jun 30, 2022 | 205,000.00 |
| Mar 31, 2022 | 71,000.00 |
| Dec 31, 2021 | 101,000.00 |
| Sep 30, 2021 | 276,000.00 |
API Access
Magyar 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=MGYR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "provision-for-losses", "ticker": "MGYR", "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=MGYR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();