Metlife (MET) Operating Expenses (2009 - 2026)
Metlife (MET) reported Operating Expenses of $18.12 billion for Q2 2026, up 10.8% from $16.36 billion a year earlier and up 3.1% from the prior quarter.
Powered by 
Analysis
Metlife (MET) Operating Expenses (2009 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Metlife's Operating Expenses came in at $74.53 billion, up 10.7% year-over-year; for FY2025, it came in at $72.42 billion, up 10.8% from FY2024.
- Operating Expenses has increased for four consecutive years, with a five-year compound annual growth rate of 3.5% (FY2020 to FY2025).
- By year, Operating Expenses came in at $65.36 billion in FY2024 (+1.0%), $64.74 billion in FY2023 (+3.7%), $62.41 billion in FY2022 (+3.7%) and $60.18 billion in FY2021 (-1.2%).
- Five-year quarterly Operating Expenses spans a low of $13.47 billion in Q1 2022 and a high of $22.7 billion in Q4 2025.
- Year over year, Operating Expenses has now increased in each of the last three quarters, with growth averaging 7.3% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q3 2022 (growth of 40.4%); the low point was Q3 2023 (a decline of 26.5%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $17.57 billion (Q1 2026), $22.7 billion (Q4 2025) and $16.15 billion (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Chubb | 138.35 Bn | 84.93 Bn | 9.13 Bn | 12.19 Bn |
| 2 | Progressive | 129.14 Bn | 104.97 Bn | 9.04 Bn | 19.40 Bn |
| 3 | Marsh & Mclennan Companies | 91.11 Bn | 83.27 Bn | - | 5.65 Bn |
| 4 | Travelers Companies | 83.32 Bn | 59.56 Bn | 6.23 Bn | 9.39 Bn |
| 5 | Manulife Financial | 75.74 Bn | -19.14 Bn | - | -902.21 Mn |
| 6 | Arthur J. Gallagher | 66.49 Bn | 60.90 Bn | - | 3.59 Bn |
| 7 | Metlife | 64.97 Bn | -41.81 Bn | 7.82 Bn | 18.12 Bn |
| 8 | Allstate | 63.98 Bn | 25.25 Bn | 8.73 Bn | 14.45 Bn |
| 9 | Aon | 63.25 Bn | 56.46 Bn | - | 3.33 Bn |
| 10 | Aflac | 60.55 Bn | 35.76 Bn | 2.27 Bn | 3.12 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 18.12 Bn |
| Mar 31, 2026 | 17.57 Bn |
| Dec 31, 2025 | 22.70 Bn |
| Sep 30, 2025 | 16.15 Bn |
| Jun 30, 2025 | 16.36 Bn |
| Mar 31, 2025 | 17.22 Bn |
| Dec 31, 2024 | 17.29 Bn |
| Sep 30, 2024 | 16.45 Bn |
| Jun 30, 2024 | 16.62 Bn |
| Mar 31, 2024 | 15.01 Bn |
| Dec 31, 2023 | 18.09 Bn |
| Sep 30, 2023 | 15.33 Bn |
| Jun 30, 2023 | 16.19 Bn |
| Mar 31, 2023 | 15.13 Bn |
| Dec 31, 2022 | 13.58 Bn |
| Sep 30, 2022 | 20.87 Bn |
| Jun 30, 2022 | 14.49 Bn |
| Mar 31, 2022 | 13.47 Bn |
| Dec 31, 2021 | 16.01 Bn |
| Sep 30, 2021 | 14.86 Bn |
API Access
Metlife 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=MET&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "MET", "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=MET&period=max&api_key=YOUR_API_KEY");
const data = await res.json();