Laureate Education (LAUR) Tax Provisions (2016 - 2026)
Laureate Education (LAUR) posted Tax Provisions of $81.67 million for Q2 2026, up 17.7% from $69.36 million a year earlier.
Laureate Education (LAUR) Tax Provisions (2016 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Tax Provisions at Laureate Education was $121.39 million, up 3.0% year-over-year; for FY2025, it came in at $117.31 million, down 1.4% from FY2024.
- Annual Tax Provisions has declined for three consecutive years.
- In prior years, Laureate Education's Tax Provisions was $118.98 million in FY2024 (-13.5%), $137.6 million in FY2023 (-25.8%), $185.39 million in FY2022 (+27.4%) and $145.57 million in FY2021.
- The Q2 2026 figure stands as the highest quarterly Tax Provisions since Q1 2021.
- On a year-over-year basis, Tax Provisions increased in three of the last five quarters, with an average decline of 19.0%.
- The strongest year-over-year quarter for Tax Provisions in the past five years was Q2 2022, with growth of 445.9%; the weakest was Q1 2023, with a decline of 78.7%.
- According to Business Quant data, Tax Provisions for the three prior quarters was -$5.71 million (Q1 2026), $10.98 million (Q4 2025) and $34.45 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Taxes (Qtr) |
|---|---|---|---|---|---|
| 1 | Service Corp International | 11.15 Bn | 10.15 Bn | 273.50 Mn | 41.94 Mn |
| 2 | New Oriental Education & Technology | 9.53 Bn | -1.61 Bn | 5,600.00 | -25.38 Mn |
| 3 | TAL Education | 7.16 Bn | -5.83 Bn | 438.20 Mn | -143.66 Mn |
| 4 | Laureate Education | 5.43 Bn | 4.73 Bn | 237.67 Mn | 81.67 Mn |
| 5 | Graham Holdings | 5.11 Bn | 202.28 Mn | 392.03 Mn | 35.10 Mn |
| 6 | Covista | 4.47 Bn | 3.59 Bn | 284.63 Mn | 16.24 Mn |
| 7 | Valvoline | 4.04 Bn | 3.75 Bn | 214.90 Mn | 20.60 Mn |
| 8 | Bright Horizons Family Solutions | 3.63 Bn | 3.07 Bn | 188.96 Mn | 25.16 Mn |
| 9 | Stride | 3.55 Bn | 446.85 Mn | 217.28 Mn | 22.83 Mn |
| 10 | Onespaworld Holdings | 2.43 Bn | 2.33 Bn | 44.57 Mn | 226,000.00 |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 81.67 Mn |
| Mar 31, 2026 | -5.71 Mn |
| Dec 31, 2025 | 10.98 Mn |
| Sep 30, 2025 | 34.45 Mn |
| Jun 30, 2025 | 69.36 Mn |
| Mar 31, 2025 | 2.52 Mn |
| Dec 31, 2024 | 46.45 Mn |
| Sep 30, 2024 | -468,000.00 |
| Jun 30, 2024 | 63.07 Mn |
| Mar 31, 2024 | 9.92 Mn |
| Dec 31, 2023 | 36.22 Mn |
| Sep 30, 2023 | 33.72 Mn |
| Jun 30, 2023 | 57.47 Mn |
| Mar 31, 2023 | 10.20 Mn |
| Dec 31, 2022 | 26.18 Mn |
| Sep 30, 2022 | 39.28 Mn |
| Jun 30, 2022 | 71.97 Mn |
| Mar 31, 2022 | 47.97 Mn |
| Dec 31, 2021 | -28.59 Mn |
| Sep 30, 2021 | 48.12 Mn |
Laureate Education 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=LAUR&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "tax-provisions", "ticker": "LAUR", "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=LAUR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();