Formula Systems (1985) (FORTY) Tax Provisions (2009 - 2026)
Formula Systems (1985)'s Tax Provisions came in at $14.06 million for Q2 2026, up 29.7% from $10.84 million a year earlier but down 8.5% from the prior quarter.
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Analysis
Formula Systems (1985) (FORTY) Tax Provisions (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Formula Systems (1985) reported Tax Provisions of $48.09 million, up 14.1% year-over-year; for FY2025, it was $40.46 million, up 4.3% from FY2024.
- Tax Provisions carries a five-year compound annual growth rate of 5.3% (FY2020 to FY2025).
- Going back by year, Tax Provisions was $38.77 million in FY2024 (+21.8%), $31.83 million in FY2023 (-42.4%), $55.24 million in FY2022 (+29.6%) and $42.61 million in FY2021 (+36.3%).
- The five-year range for quarterly Tax Provisions is $6.71 million (Q4 2025) to $21.42 million (Q2 2022).
- Year-over-year, Tax Provisions increased in four of the last eight quarters, with an average decline of 0.6%.
- The fastest year-over-year change in Tax Provisions over five years came in Q2 2022 (growth of 97.5%), and the weakest in Q2 2023 (a decline of 46.9%).
- Business Quant data shows FORTY's Tax Provisions at $15.38 million (Q1 2026), $6.71 million (Q4 2025) and $11.94 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Taxes (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 50.59 Bn | 37.09 Bn | 1.60 Bn | 343.00 Mn |
| 2 | Cognizant Technology Solutions | 32.87 Bn | 26.04 Bn | 1.83 Bn | 231.00 Mn |
| 3 | Wipro | 22.10 Bn | 17.25 Bn | 745.00 Mn | -105.00 Mn |
| 4 | Cdw | 20.94 Bn | 18.92 Bn | 1.32 Bn | 99.00 Mn |
| 5 | Td Synnex | 19.62 Bn | 13.78 Bn | 1.43 Bn | 139.01 Mn |
| 6 | Cgi | 18.25 Bn | 16.05 Bn | - | 121.97 Mn |
| 7 | Arrow Electronics | 10.72 Bn | 9.67 Bn | 1.13 Bn | 80.31 Mn |
| 8 | Avnet | 7.23 Bn | 6.41 Bn | 865.03 Mn | 33.58 Mn |
| 9 | EPAM Systems | 7.08 Bn | 2.72 Bn | 429.57 Mn | 37.57 Mn |
| 10 | Formula Systems (1985) | 1.79 Bn | -1.56 Bn | 158.43 Mn | 14.06 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 14.06 Mn |
| Mar 31, 2026 | 15.38 Mn |
| Dec 31, 2025 | 6.71 Mn |
| Sep 30, 2025 | 11.94 Mn |
| Jun 30, 2025 | 10.84 Mn |
| Mar 31, 2025 | 10.97 Mn |
| Dec 31, 2024 | 10.76 Mn |
| Sep 30, 2024 | 9.60 Mn |
| Jun 30, 2024 | 13.65 Mn |
| Mar 31, 2024 | 13.46 Mn |
| Dec 31, 2023 | 10.72 Mn |
| Sep 30, 2023 | 12.49 Mn |
| Jun 30, 2023 | 11.38 Mn |
| Mar 31, 2023 | 11.49 Mn |
| Dec 31, 2022 | 10.91 Mn |
| Sep 30, 2022 | 11.41 Mn |
| Jun 30, 2022 | 21.42 Mn |
| Mar 31, 2022 | 11.50 Mn |
| Dec 31, 2021 | 12.60 Mn |
| Sep 30, 2021 | 9.82 Mn |
API Access
Formula Systems (1985) Tax Provisions 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=tax-provisions&ticker=FORTY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "tax-provisions", "ticker": "FORTY", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=tax-provisions&ticker=FORTY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();