Slm (SLM) Provision for Credit Losses (2009 - 2026)
Slm (SLM) reported Provision for Credit Losses of $103.06 million for Q3 2026, down 28.2% from $143.5 million a year earlier but up 50.8% from the prior quarter.
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Analysis
Slm (SLM) Provision for Credit Losses (2009 - 2026) Analysis & Trends
Over the twelve months ended Sep 30, 2026, Slm's Provision for Credit Losses came in at $314.29 million, down 31.6% year-over-year; for FY2025, it was $400.68 million, down 2.0% from FY2024.
- By year, Provision for Credit Losses came in at $409 million in FY2024 (+68.6%), $242.57 million in FY2023 (-41.3%), $413.54 million in FY2022 (+77.7%) and $232.71 million in FY2021.
- Five-year quarterly Provision for Credit Losses spans a low of -$15.31 million in Q4 2021 and a high of $297.26 million in Q4 2022.
- Year over year, Provision for Credit Losses has now declined in each of the last four quarters, with growth averaging 81.9% over the last eight quarters.
- The high point for year-over-year Provision for Credit Losses in five years was Q4 2024 (growth of 723.5%); the low point was Q4 2023 (a decline of 94.8%).
- Per Business Quant data, the three quarters before Q3 2026 came in at $68.33 million (Q2 2026), $73.2 million (Q1 2026) and $69.7 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Provisions (Qtr) |
|---|---|---|---|---|---|
| 1 | Rocket Companies | 41.00 Bn | 29.82 Bn | - | - |
| 2 | Royalty Pharma | 39.88 Bn | 40.21 Bn | - | -88.32 Mn |
| 3 | Orix | 36.75 Bn | 7.39 Bn | 13.83 Bn | 14.87 Mn |
| 4 | Federal National Mortgage Association Fannie Mae | 25.40 Bn | -16,108.71 Bn | - | 1.14 Bn |
| 5 | Royal Gold | 23.20 Bn | 22.41 Bn | 402.46 Mn | - |
| 6 | Affirm Holdings | 22.35 Bn | 15.40 Bn | - | 259.36 Mn |
| 7 | Synchrony Financial | 22.29 Bn | -45.34 Bn | - | 1.27 Bn |
| 8 | Annaly Capital Management | 14.69 Bn | 5.72 Bn | - | - |
| 9 | Ares Capital | 14.04 Bn | 11.79 Bn | - | - |
| 10 | Slm | 3.07 Bn | -13.28 Bn | - | 103.06 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 103.06 Mn |
| Jun 30, 2026 | 68.33 Mn |
| Mar 31, 2026 | 73.20 Mn |
| Dec 31, 2025 | 69.70 Mn |
| Sep 30, 2025 | 143.50 Mn |
| Jun 30, 2025 | 92.19 Mn |
| Mar 31, 2025 | 95.29 Mn |
| Dec 31, 2024 | 128.46 Mn |
| Sep 30, 2024 | 113.56 Mn |
| Jun 30, 2024 | 72.42 Mn |
| Mar 31, 2024 | 94.56 Mn |
| Dec 31, 2023 | 15.60 Mn |
| Sep 30, 2023 | 45.09 Mn |
| Jun 30, 2023 | 96.19 Mn |
| Mar 31, 2023 | 57.80 Mn |
| Dec 31, 2022 | 297.26 Mn |
| Sep 30, 2022 | 207.60 Mn |
| Jun 30, 2022 | 30.55 Mn |
| Mar 31, 2022 | 98.05 Mn |
| Dec 31, 2021 | -15.31 Mn |
API Access
Slm 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=SLM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "provision-for-credit-losses", "ticker": "SLM", "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=SLM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();