Green Dot (GDOT) Operating Expenses (2010 - 2026)
Green Dot's Operating Expenses was $596.64 million in Q2 2026, up 21.6% from $490.78 million a year earlier and up 1.6% from the prior quarter.
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Analysis
Green Dot (GDOT) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Green Dot's Operating Expenses was $2.26 billion through Jun 30, 2026, up 22.8% year-over-year; for FY2025, it came in at $2.07 billion, up 19.8% from FY2024.
- Operating Expenses has now increased for three consecutive years, with a five-year compound annual growth rate of 11.1% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $1.73 billion in FY2024 (+16.7%), $1.48 billion in FY2023 (+9.1%), $1.36 billion in FY2022 (-0.8%) and $1.37 billion in FY2021 (+11.7%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses in data going back to Q2 2010.
- Compared with a year earlier, Operating Expenses has increased for 14 straight quarters, with growth averaging 18.2% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q3 2025 (growth of 27.9%); the worst was Q1 2022 (a decline of 2.9%).
- Per Business Quant data, GDOT's Operating Expenses in the three quarters before Q2 2026 was $587.21 million (Q1 2026), $550.27 million (Q4 2025) and $527.66 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 896.53 Bn | 896.53 Bn | - | 27.30 Bn |
| 2 | Bank Of America | 354.20 Bn | -2,021.91 Bn | - | 19.72 Bn |
| 3 | Hsbc Holdings | 303.54 Bn | -1,800.05 Bn | - | 8.82 Bn |
| 4 | Royal Bank Of Canada | 283.29 Bn | -546.75 Bn | - | 7.02 Bn |
| 5 | Morgan Stanley | 281.19 Bn | -262.84 Bn | - | 13.71 Bn |
| 6 | Goldman Sachs | 256.26 Bn | -3,487.19 Bn | - | 11.31 Bn |
| 7 | Wells Fargo & Company | 253.33 Bn | 253.33 Bn | - | 13.74 Bn |
| 8 | Mitsubishi Ufj Financial | 238.77 Bn | -102.62 Bn | 10.89 Bn | 17.50 Bn |
| 9 | American Express | 216.03 Bn | 15.51 Bn | - | 14.55 Bn |
| 10 | Green Dot | 694.80 Mn | -5.15 Bn | - | 596.64 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 596.64 Mn |
| Mar 31, 2026 | 587.21 Mn |
| Dec 31, 2025 | 550.27 Mn |
| Sep 30, 2025 | 527.66 Mn |
| Jun 30, 2025 | 490.78 Mn |
| Mar 31, 2025 | 498.13 Mn |
| Dec 31, 2024 | 440.65 Mn |
| Sep 30, 2024 | 412.68 Mn |
| Jun 30, 2024 | 430.79 Mn |
| Mar 31, 2024 | 441.43 Mn |
| Dec 31, 2023 | 392.32 Mn |
| Sep 30, 2023 | 359.87 Mn |
| Jun 30, 2023 | 361.09 Mn |
| Mar 31, 2023 | 365.39 Mn |
| Dec 31, 2022 | 334.35 Mn |
| Sep 30, 2022 | 332.98 Mn |
| Jun 30, 2022 | 338.83 Mn |
| Mar 31, 2022 | 349.03 Mn |
| Dec 31, 2021 | 338.98 Mn |
| Sep 30, 2021 | 330.67 Mn |
API Access
Green Dot 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=GDOT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "GDOT", "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=GDOT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();