Federal National Mortgage Association Fannie Mae (FNMAJ) Provision for Credit Losses (2009 - 2026)
Federal National Mortgage Association Fannie Mae (FNMAJ) reported Provision for Credit Losses of $1.14 billion for Q3 2026, up 237.3% from $338 million a year earlier and up 135.1% from the prior quarter.
Federal National Mortgage Association Fannie Mae (FNMAJ) Provision for Credit Losses (2009 - 2026) Analysis & Trends
Over the twelve months ended Sep 30, 2026, Federal National Mortgage Association Fannie Mae's Provision for Credit Losses came in at $2.2 billion, up 35.1% year-over-year; for FY2025, it came in at $1.61 billion.
- Provision for Credit Losses has a five-year compound annual growth rate of 18.8% (FY2020 to FY2025).
- By year, Provision for Credit Losses came in at -$186 million in FY2024, -$1.67 billion in FY2023, $6.31 billion in FY2022 and -$5.13 billion in FY2021.
- The Q3 2026 figure ranks as the highest quarterly Provision for Credit Losses since Q4 2022.
- Year over year, Provision for Credit Losses gained in two of the last four quarters, with growth averaging 89.5%.
- Per Business Quant data, the three quarters before Q3 2026 came in at $485 million (Q2 2026), $277 million (Q1 2026) and $298 million (Q4 2025).
Peer Comparison
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 1.14 Bn |
| Jun 30, 2026 | 485.00 Mn |
| Mar 31, 2026 | 277.00 Mn |
| Dec 31, 2025 | 298.00 Mn |
| Sep 30, 2025 | 338.00 Mn |
| Jun 30, 2025 | 946.00 Mn |
| Mar 31, 2025 | 24.00 Mn |
| Dec 31, 2024 | 321.00 Mn |
| Sep 30, 2024 | -27.00 Mn |
| Jun 30, 2024 | -300.00 Mn |
| Mar 31, 2024 | -182.00 Mn |
| Dec 31, 2023 | 116.00 Mn |
| Sep 30, 2023 | -652.00 Mn |
| Jun 30, 2023 | -1.27 Bn |
| Mar 31, 2023 | 176.00 Mn |
| Dec 31, 2022 | 3.28 Bn |
| Sep 30, 2022 | 2.54 Bn |
| Jun 30, 2022 | 260.00 Mn |
| Mar 31, 2022 | 254.00 Mn |
| Dec 31, 2021 | -840.00 Mn |
Federal National Mortgage Association Fannie Mae Provision for Credit 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-credit-losses&ticker=FNMAJ&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "provision-for-credit-losses", "ticker": "FNMAJ", "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-credit-losses&ticker=FNMAJ&period=max&api_key=YOUR_API_KEY");
const data = await res.json();