Expensify (EXFY) Shares Outstanding (Diluted) (2020 - 2026)
Expensify (EXFY) recorded Shares Outstanding (Diluted) of 95.44 million in Q2 2026, up 3.4% from 92.27 million a year earlier and up 1.8% from the prior quarter.
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Analysis
Expensify (EXFY) Shares Outstanding (Diluted) (2020 - 2026) Analysis & Trends
For FY2025, Expensify reported Shares Outstanding (Diluted) of 92.28 million, up 5.6% from FY2024.
- Annual Shares Outstanding (Diluted) has increased for six straight years, with a five-year compound annual growth rate of 27.5% (FY2020 to FY2025).
- Across earlier years, Shares Outstanding (Diluted) came in at 87.38 million in FY2024 (+5.9%), 82.49 million in FY2023 (+2.1%), 80.79 million in FY2022 (+112.4%) and 38.04 million in FY2021 (+38.7%).
- The Q2 2026 figure is the highest quarterly Shares Outstanding (Diluted) in data going back to Q3 2020.
- On a year-over-year basis, Shares Outstanding (Diluted) has increased for 20 consecutive quarters, with growth averaging 5.4% over the last eight quarters.
- Across the past five years, year-over-year growth in Shares Outstanding (Diluted) ran from 1.9% in Q3 2023 to 134.7% in Q3 2022.
- Per Business Quant, the preceding three quarters came in at 93.72 million (Q1 2026), 92.28 million (Q4 2025) and 92.56 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Shares Outstanding (Dil.) (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 406.36 Bn | 371.19 Bn | 1.93 Bn | 2.57 Bn |
| 2 | Oracle | 350.97 Bn | 223.10 Bn | - | 3.00 Bn |
| 3 | Sap Se | 276.32 Bn | 203.72 Bn | 8.64 Bn | 1.18 Bn |
| 4 | Salesforce | 175.73 Bn | 131.60 Bn | 8.70 Bn | 821.00 Mn |
| 5 | Automatic Data Processing | 121.62 Bn | 108.41 Bn | 2.53 Bn | 403.30 Mn |
| 6 | ServiceNow | 107.21 Bn | 86.47 Bn | 2.90 Bn | 1.04 Bn |
| 7 | Intuit | 93.23 Bn | 72.58 Bn | 3.44 Bn | 277.00 Mn |
| 8 | Relx | 73.21 Bn | 72.30 Bn | - | 1.84 Bn |
| 9 | Strategy | 50.23 Bn | 37.36 Bn | 89.63 Mn | 428.05 Mn |
| 10 | Expensify | 171.62 Mn | -87.50 Mn | 14.93 Mn | 91.53 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 91.53 Mn |
| Jun 30, 2026 | 95.44 Mn |
| Mar 31, 2026 | 93.72 Mn |
| Dec 31, 2025 | 92.28 Mn |
| Sep 30, 2025 | 92.56 Mn |
| Jun 30, 2025 | 92.27 Mn |
| Mar 31, 2025 | 91.50 Mn |
| Dec 31, 2024 | 87.38 Mn |
| Sep 30, 2024 | 88.18 Mn |
| Jun 30, 2024 | 86.59 Mn |
| Mar 31, 2024 | 85.14 Mn |
| Dec 31, 2023 | 82.49 Mn |
| Sep 30, 2023 | 82.47 Mn |
| Jun 30, 2023 | 82.01 Mn |
| Mar 31, 2023 | 81.77 Mn |
| Dec 31, 2022 | 80.79 Mn |
| Sep 30, 2022 | 80.94 Mn |
| Jun 30, 2022 | 80.47 Mn |
| Mar 31, 2022 | 80.15 Mn |
| Dec 31, 2021 | 38.04 Mn |
API Access
Expensify Shares Outstanding (Diluted) 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=shares-outstanding-diluted&ticker=EXFY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "shares-outstanding-diluted", "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=shares-outstanding-diluted&ticker=EXFY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();