Loews (L) Operating Expenses (2009 - 2026)
Loews (L) posted Operating Expenses of $4.12 billion for Q2 2026, up 2.6% from $4.02 billion a year earlier and up 0.7% from the prior quarter.
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Analysis
Loews (L) Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Loews was $16.39 billion, up 0.7% year-over-year; for FY2025, it came in at $16.17 billion, up 3.4% from FY2024.
- Annual Operating Expenses has increased for four consecutive years, with a five-year compound annual growth rate of 2.9% (FY2020 to FY2025).
- In prior years, Loews' Operating Expenses was $15.64 billion in FY2024 (+12.4%), $13.91 billion in FY2023 (+7.5%), $12.93 billion in FY2022 (+3.5%) and $12.5 billion in FY2021 (-11.0%).
- Quarterly Operating Expenses has run from a low of $2.96 billion in Q1 2022 to a high of $4.36 billion in Q4 2024 over five years.
- On a year-over-year basis, Operating Expenses increased in seven of the last eight quarters, with growth averaging 6.2%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q4 2024, with growth of 19.6%; the weakest was Q1 2022, with a decline of 7.8%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $4.09 billion (Q1 2026), $4.19 billion (Q4 2025) and $3.98 billion (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Chubb | 134.07 Bn | 80.65 Bn | 9.13 Bn | 12.19 Bn |
| 2 | Progressive | 129.71 Bn | 105.55 Bn | 9.04 Bn | 19.40 Bn |
| 3 | Marsh & Mclennan Companies | 85.23 Bn | 76.72 Bn | - | 5.51 Bn |
| 4 | Travelers Companies | 78.57 Bn | 54.82 Bn | 6.23 Bn | 9.39 Bn |
| 5 | Manulife Financial | 73.77 Bn | -21.12 Bn | - | -902.21 Mn |
| 6 | Metlife | 64.61 Bn | -42.17 Bn | 7.82 Bn | 18.12 Bn |
| 7 | Allstate | 60.51 Bn | 21.78 Bn | 8.73 Bn | 14.45 Bn |
| 8 | Arthur J. Gallagher | 59.88 Bn | 54.28 Bn | - | 3.59 Bn |
| 9 | Aflac | 58.72 Bn | 33.93 Bn | 2.27 Bn | 3.12 Bn |
| 10 | Loews | 22.32 Bn | 18.30 Mn | 2.57 Bn | 4.12 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 4.12 Bn |
| Mar 31, 2026 | 4.09 Bn |
| Dec 31, 2025 | 4.19 Bn |
| Sep 30, 2025 | 3.98 Bn |
| Jun 30, 2025 | 4.02 Bn |
| Mar 31, 2025 | 3.98 Bn |
| Dec 31, 2024 | 4.36 Bn |
| Sep 30, 2024 | 3.92 Bn |
| Jun 30, 2024 | 3.76 Bn |
| Mar 31, 2024 | 3.60 Bn |
| Dec 31, 2023 | 3.65 Bn |
| Sep 30, 2023 | 3.57 Bn |
| Jun 30, 2023 | 3.43 Bn |
| Mar 31, 2023 | 3.26 Bn |
| Dec 31, 2022 | 3.33 Bn |
| Sep 30, 2022 | 3.49 Bn |
| Jun 30, 2022 | 3.15 Bn |
| Mar 31, 2022 | 2.96 Bn |
| Dec 31, 2021 | 3.22 Bn |
| Sep 30, 2021 | 3.07 Bn |
API Access
Loews 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=L&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "L", "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=L&period=max&api_key=YOUR_API_KEY");
const data = await res.json();