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Marsh & McLennan Companies, Inc.: operating expenses

Operating expenses for Marsh & McLennan Companies, Inc. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All Marsh & McLennan Companies, Inc. financial histories

What this measure means

Recurring operating costs under this accounting concept, generally excluding production costs included in cost of sales. Check filing presentation before combining expense subtotals.

Exact concept: us-gaap:OperatingExpenses. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2007-01-01 to 2025-12-31. The SEC response was captured on 2026-09-19.

Selected filing history

Operating expenses in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-3120,758,000,000USD2026-02-0910-K · 0000062709-26-000022
2024-01-012024-12-3118,641,000,000USD2026-02-0910-K · 0000062709-26-000022
2023-01-012023-12-3117,454,000,000USD2026-02-0910-K · 0000062709-26-000022
2022-01-012022-12-3116,440,000,000USD2025-02-1010-K · 0000062709-25-000015
2021-01-012021-12-3115,508,000,000USD2024-02-1210-K · 0000062709-24-000016
2020-01-012020-12-3114,158,000,000USD2023-02-1310-K · 0000062709-23-000014
2019-01-012019-12-3113,975,000,000USD2022-02-1610-K · 0000062709-22-000009
2018-01-012018-12-3112,189,000,000USD2021-02-1710-K · 0000062709-21-000008
2017-01-012017-12-3111,369,000,000USD2020-02-2010-K · 0000062709-20-000010
2016-01-012016-12-3110,780,000,000USD2019-02-2110-K · 0000062709-19-000010
2015-01-012015-12-3110,474,000,000USD2018-02-2210-K · 0000062709-18-000007
2014-01-012014-12-3110,650,000,000USD2017-02-2410-K · 0000062709-17-000008
2013-01-012013-12-3110,184,000,000USD2016-02-2410-K · 0000062709-16-000040
2012-01-012012-12-3110,095,000,000USD2015-02-2610-K · 0000062709-15-000005
2011-01-012011-12-319,888,000,000USD2014-02-2710-K · 0000062709-14-000008
2010-01-012010-12-319,611,000,000USD2013-02-2710-K · 0000062709-13-000004
2009-01-012009-12-319,053,000,000USD2012-02-2810-K · 0000062709-12-000016
2008-01-012008-12-3110,051,000,000USD2011-02-2810-K · 0001193125-11-047795
2007-01-012007-12-3110,281,000,000USD2010-02-2610-K · 0001193125-10-042765

Related financial histories

Inspect the source

Entity
Marsh & McLennan Companies, Inc. / CIK 0000062709
Captured
2026-09-19T14:49:05.432Z
SEC response SHA-256
ad691a077f6a124aa14b0954da357a14aa7be1638dbb7fd40d0aa1c9c6df50b7

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0000062709.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))