Security Federal (SFDL) Operating Expenses (2009 - 2025)
Security Federal (SFDL) posted Operating Expenses of $11.05 million for Q4 2025, up 16.0% from $9.52 million a year earlier and up 6.7% from the prior quarter.
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Analysis
Security Federal (SFDL) Operating Expenses (2009 - 2025) Analysis & Trends
For FY2025, Security Federal's Operating Expenses came in at $41.6 million, up 9.1% from FY2024.
- Annual Operating Expenses has increased for three consecutive years, with a five-year compound annual growth rate of 3.4% (FY2020 to FY2025).
- In prior years, Security Federal's Operating Expenses was $38.14 million in FY2024 (+6.2%), $35.91 million in FY2023 (+4.9%), $34.23 million in FY2022 (-9.5%) and $37.81 million in FY2021 (+7.5%).
- The Q4 2025 figure stands as the highest quarterly Operating Expenses in data going back to Q2 2013.
- On a year-over-year basis, Operating Expenses has increased in each of the last 11 quarters, with growth averaging 7.7% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q4 2021, with growth of 17.8%; the weakest was Q4 2022, with a decline of 14.4%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $10.35 million (Q3 2025), $10.36 million (Q2 2025) and $9.84 million (Q1 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 909.02 Bn | 886.77 Bn | - | 27.30 Bn |
| 2 | Banco Santander Chile | 406.67 Bn | -7,110.43 Bn | - | - |
| 3 | Bank Of America | 350.91 Bn | -2,025.20 Bn | - | 19.72 Bn |
| 4 | Hsbc Holdings | 308.71 Bn | -2,966.46 Bn | - | 8.82 Bn |
| 5 | Morgan Stanley | 293.66 Bn | -249.15 Bn | - | 13.71 Bn |
| 6 | Royal Bank Of Canada | 283.56 Bn | -546.44 Bn | - | 7.02 Bn |
| 7 | Goldman Sachs | 262.71 Bn | -3,480.74 Bn | - | 11.31 Bn |
| 8 | Wells Fargo & Company | 257.44 Bn | 92.87 Bn | - | 13.74 Bn |
| 9 | Mitsubishi Ufj Financial | 256.82 Bn | -75.42 Bn | 10.89 Bn | 17.50 Bn |
| 10 | Security Federal | 146.35 Mn | -261.06 Mn | - | 11.05 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2025 | 11.05 Mn |
| Sep 30, 2025 | 10.35 Mn |
| Jun 30, 2025 | 10.36 Mn |
| Mar 31, 2025 | 9.84 Mn |
| Dec 31, 2024 | 9.52 Mn |
| Sep 30, 2024 | 9.31 Mn |
| Jun 30, 2024 | 9.67 Mn |
| Mar 31, 2024 | 9.64 Mn |
| Dec 31, 2023 | 9.05 Mn |
| Sep 30, 2023 | 8.92 Mn |
| Jun 30, 2023 | 8.91 Mn |
| Mar 31, 2023 | 9.03 Mn |
| Dec 31, 2022 | 8.92 Mn |
| Sep 30, 2022 | 8.28 Mn |
| Jun 30, 2022 | 8.43 Mn |
| Mar 31, 2022 | 8.59 Mn |
| Dec 31, 2021 | 8.94 Mn |
| Sep 30, 2021 | 8.05 Mn |
| Jun 30, 2021 | 7.45 Mn |
| Mar 31, 2021 | 7.61 Mn |
API Access
Security Federal Operating Expenses 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=operating-expenses&ticker=SFDL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SFDL", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=SFDL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();