Expensify (EXFY) Operating Expenses (2020 - 2026)
Expensify (EXFY) reported Operating Expenses of $19.25 million for Q2 2026, down 33.4% from $28.92 million a year earlier but up 6.1% from the prior quarter.
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Analysis
Expensify (EXFY) Operating Expenses (2020 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Expensify's Operating Expenses came in at $78.3 million, down 7.9% year-over-year; for FY2025, it was $89.55 million, up 18.1% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of 12.4% (FY2020 to FY2025).
- By year, Operating Expenses came in at $75.82 million in FY2024 (-35.2%), $116.95 million in FY2023 (-4.2%), $122.06 million in FY2022 (+22.8%) and $99.39 million in FY2021 (+98.8%).
- Five-year quarterly Operating Expenses spans a low of $17.98 million in Q3 2024 and a high of $40.87 million in Q4 2021.
- Year over year, Operating Expenses gained in three of the last eight quarters, with an average decline of 4.9%.
- The high point for year-over-year Operating Expenses in five years was Q4 2021 (growth of 219.0%); the low point was Q3 2024 (a decline of 46.7%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $18.14 million (Q1 2026), $21.25 million (Q4 2025) and $19.66 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 450.50 Bn | 419.56 Bn | 1.64 Bn | 726.59 Mn |
| 2 | Oracle | 401.01 Bn | 273.57 Bn | - | 12.62 Bn |
| 3 | Sap Se | 257.03 Bn | 178.11 Bn | 8.40 Bn | -8.41 Bn |
| 4 | Salesforce | 187.04 Bn | 142.92 Bn | 8.70 Bn | 6.37 Bn |
| 5 | ServiceNow | 135.91 Bn | 114.37 Bn | 2.82 Bn | 2.66 Bn |
| 6 | Automatic Data Processing | 104.14 Bn | 86.27 Bn | 2.51 Bn | 4.34 Bn |
| 7 | Intuit | 72.30 Bn | 51.65 Bn | 3.44 Bn | 3.88 Bn |
| 8 | Relx | 60.17 Bn | 57.14 Bn | - | - |
| 9 | Strategy | 55.31 Bn | 48.30 Bn | 81.55 Mn | 8.41 Bn |
| 10 | Expensify | 197.58 Mn | -59.24 Mn | 16.33 Mn | 19.25 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 19.25 Mn |
| Mar 31, 2026 | 18.14 Mn |
| Dec 31, 2025 | 21.25 Mn |
| Sep 30, 2025 | 19.66 Mn |
| Jun 30, 2025 | 28.92 Mn |
| Mar 31, 2025 | 19.73 Mn |
| Dec 31, 2024 | 18.39 Mn |
| Sep 30, 2024 | 17.98 Mn |
| Jun 30, 2024 | 18.71 Mn |
| Mar 31, 2024 | 20.74 Mn |
| Dec 31, 2023 | 24.69 Mn |
| Sep 30, 2023 | 33.71 Mn |
| Jun 30, 2023 | 31.52 Mn |
| Mar 31, 2023 | 27.03 Mn |
| Dec 31, 2022 | 28.06 Mn |
| Sep 30, 2022 | 31.66 Mn |
| Jun 30, 2022 | 31.26 Mn |
| Mar 31, 2022 | 31.08 Mn |
| Dec 31, 2021 | 40.87 Mn |
| Sep 30, 2021 | 28.11 Mn |
API Access
Expensify 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=EXFY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "EXFY", "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=EXFY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();