Jones Lang Lasalle (JLL) Tax Provisions (2009 - 2026)
Jones Lang Lasalle (JLL) reported Tax Provisions of $51.3 million for Q2 2026, up 92.1% from $26.7 million a year earlier and up 34.6% from the prior quarter.
Powered by 
Analysis
Jones Lang Lasalle (JLL) Tax Provisions (2009 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Jones Lang Lasalle's Tax Provisions came in at $238.2 million, up 74.1% year-over-year; for FY2025, it came in at $189.5 million, up 43.0% from FY2024.
- Tax Provisions has a five-year compound annual growth rate of 12.1% (FY2020 to FY2025).
- By year, Tax Provisions came in at $132.5 million in FY2024 (+415.6%), $25.7 million in FY2023 (-87.2%), $200.8 million in FY2022 (-24.0%) and $264.3 million in FY2021 (+147.2%).
- Five-year quarterly Tax Provisions spans a low of -$2.3 million in Q1 2023 and a high of $115.9 million in Q4 2021.
- Year over year, Tax Provisions has now increased in each of the last five quarters, with growth averaging 113.4% over the last eight quarters.
- The high point for year-over-year Tax Provisions in five years was Q4 2024 (growth of 362.2%); the low point was Q2 2023 (a decline of 98.9%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $38.1 million (Q1 2026), $96.2 million (Q4 2025) and $52.6 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Taxes (Qtr) |
|---|---|---|---|---|---|
| 1 | KE Holdings | 37.89 Bn | 18.60 Bn | 1.03 Bn | -139.88 Mn |
| 2 | Cbre | 37.24 Bn | 31.01 Bn | 2.09 Bn | 68.00 Mn |
| 3 | Jones Lang Lasalle | 14.06 Bn | 12.27 Bn | - | 51.30 Mn |
| 4 | Compass | 6.70 Bn | 5.16 Bn | - | 5.00 Mn |
| 5 | Colliers International | 4.59 Bn | 3.66 Bn | 635.11 Mn | 26.84 Mn |
| 6 | Cushman & Wakefield | 2.77 Bn | 247.78 Mn | 512.00 Mn | 24.60 Mn |
| 7 | Newmark | 1.95 Bn | 1.33 Bn | - | 9.58 Mn |
| 8 | Marcus & Millichap | 1.08 Bn | 173.61 Mn | - | 2.36 Mn |
| 9 | Agnt | 613.32 Mn | 143.01 Mn | 98.80 Mn | 5.00 Mn |
| 10 | Rmr | 580.01 Mn | 504.47 Mn | - | 1.90 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 51.30 Mn |
| Mar 31, 2026 | 38.10 Mn |
| Dec 31, 2025 | 96.20 Mn |
| Sep 30, 2025 | 52.60 Mn |
| Jun 30, 2025 | 26.70 Mn |
| Mar 31, 2025 | 14.00 Mn |
| Dec 31, 2024 | 58.70 Mn |
| Sep 30, 2024 | 37.40 Mn |
| Jun 30, 2024 | 20.50 Mn |
| Mar 31, 2024 | 15.90 Mn |
| Dec 31, 2023 | 12.70 Mn |
| Sep 30, 2023 | 14.50 Mn |
| Jun 30, 2023 | 800,000.00 |
| Mar 31, 2023 | -2.30 Mn |
| Dec 31, 2022 | 45.40 Mn |
| Sep 30, 2022 | 42.30 Mn |
| Jun 30, 2022 | 72.80 Mn |
| Mar 31, 2022 | 40.30 Mn |
| Dec 31, 2021 | 115.90 Mn |
| Sep 30, 2021 | 65.30 Mn |
API Access
Jones Lang Lasalle 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=JLL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "tax-provisions", "ticker": "JLL", "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=JLL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();