SoFi Technologies (SOFI) Operating Expenses (2020 - 2026)
SoFi Technologies' Operating Expenses was $1 billion in Q2 2026, up 36.6% from $732.72 million a year earlier and up 12.2% from the prior quarter.
SoFi Technologies (SOFI) Operating Expenses (2020 - 2026) Analysis & Trends
On a trailing twelve-month basis, SoFi Technologies' Operating Expenses was $3.53 billion through Jun 30, 2026, up 30.1% year-over-year; for FY2025, it was $3.06 billion, up 26.9% from FY2024.
- Operating Expenses has now increased for six consecutive years, with a five-year compound annual growth rate of 27.9% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $2.41 billion in FY2024 (+1.7%), $2.37 billion in FY2023 (+28.9%), $1.84 billion in FY2022 (+25.4%) and $1.47 billion in FY2021 (+64.0%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses in data going back to Q2 2020.
- Compared with a year earlier, Operating Expenses has increased for seven straight quarters, with growth averaging 22.9% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q3 2022 (growth of 65.1%); the worst was Q3 2024 (a decline of 22.0%).
- Per Business Quant data, SOFI's Operating Expenses in the three quarters before Q2 2026 was $891.92 million (Q1 2026), $834.31 million (Q4 2025) and $803.85 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 885.23 Bn | 914.70 Bn | - | 27.32 Bn |
| 2 | Banco Santander Chile | 404.41 Bn | 524.35 Bn | - | -3,218.32 Bn |
| 3 | Bank Of America | 381.15 Bn | -1,994.92 Bn | - | 18.63 Bn |
| 4 | Hsbc Holdings | 319.39 Bn | 319.44 Bn | - | - |
| 5 | Morgan Stanley | 298.67 Bn | -210.43 Bn | - | 13.90 Bn |
| 6 | Royal Bank Of Canada | 268.75 Bn | -557.52 Bn | - | 7.02 Bn |
| 7 | Mitsubishi Ufj Financial | 265.72 Bn | -107.91 Bn | 10.89 Bn | 17.50 Bn |
| 8 | Goldman Sachs | 261.04 Bn | -3,296.07 Bn | - | 11.67 Bn |
| 9 | Wells Fargo & Company | 253.09 Bn | 255.22 Bn | - | 13.66 Bn |
| 10 | SoFi Technologies | 20.39 Bn | 5.68 Bn | 1.02 Bn | 1.00 Bn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.00 Bn |
| Mar 31, 2026 | 891.92 Mn |
| Dec 31, 2025 | 834.31 Mn |
| Sep 30, 2025 | 803.85 Mn |
| Jun 30, 2025 | 732.72 Mn |
| Mar 31, 2025 | 686.30 Mn |
| Dec 31, 2024 | 667.32 Mn |
| Sep 30, 2024 | 627.25 Mn |
| Jun 30, 2024 | 571.64 Mn |
| Mar 31, 2024 | 543.59 Mn |
| Dec 31, 2023 | 509.30 Mn |
| Sep 30, 2023 | 804.14 Mn |
| Jun 30, 2023 | 547.35 Mn |
| Mar 31, 2023 | 508.22 Mn |
| Dec 31, 2022 | 441.30 Mn |
| Sep 30, 2022 | 498.44 Mn |
| Jun 30, 2022 | 458.24 Mn |
| Mar 31, 2022 | 439.95 Mn |
| Dec 31, 2021 | 395.06 Mn |
| Sep 30, 2021 | 301.87 Mn |
SoFi Technologies 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=SOFI&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SOFI", "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=SOFI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();