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Marsh & McLennan (STU:MSN) Debt-to-EBITDA : 2.70 (As of Sep. 2024)


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What is Marsh & McLennan Debt-to-EBITDA?

Debt-to-EBITDA measures a company's ability to pay off its debt.

Marsh & McLennan's Short-Term Debt & Capital Lease Obligation for the quarter that ended in Sep. 2024 was €749 Mil. Marsh & McLennan's Long-Term Debt & Capital Lease Obligation for the quarter that ended in Sep. 2024 was €12,567 Mil. Marsh & McLennan's annualized EBITDA for the quarter that ended in Sep. 2024 was €4,934 Mil. Marsh & McLennan's annualized Debt-to-EBITDA for the quarter that ended in Sep. 2024 was 2.70.

A high Debt-to-EBITDA ratio generally means that a company may spend more time to paying off its debt. According to Joel Tillinghast's BIG MONEY THINKS SMALL: Biases, Blind Spots, and Smarter Investing, a ratio of Debt-to-EBITDA exceeding four is usually considered scary unless tangible assets cover the debt.

The historical rank and industry rank for Marsh & McLennan's Debt-to-EBITDA or its related term are showing as below:

STU:MSN' s Debt-to-EBITDA Range Over the Past 10 Years
Min: 1.3   Med: 2.18   Max: 3.94
Current: 2.21

During the past 13 years, the highest Debt-to-EBITDA Ratio of Marsh & McLennan was 3.94. The lowest was 1.30. And the median was 2.18.

STU:MSN's Debt-to-EBITDA is ranked worse than
75% of 296 companies
in the Insurance industry
Industry Median: 1.08 vs STU:MSN: 2.21

Marsh & McLennan Debt-to-EBITDA Historical Data

The historical data trend for Marsh & McLennan's Debt-to-EBITDA can be seen below:

* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.

* Premium members only.

Marsh & McLennan Debt-to-EBITDA Chart

Marsh & McLennan Annual Data
Trend Dec14 Dec15 Dec16 Dec17 Dec18 Dec19 Dec20 Dec21 Dec22 Dec23
Debt-to-EBITDA
Get a 7-Day Free Trial Premium Member Only Premium Member Only 3.94 3.35 2.44 2.56 2.44

Marsh & McLennan Quarterly Data
Dec19 Mar20 Jun20 Sep20 Dec20 Mar21 Jun21 Sep21 Dec21 Mar22 Jun22 Sep22 Dec22 Mar23 Jun23 Sep23 Dec23 Mar24 Jun24 Sep24
Debt-to-EBITDA Get a 7-Day Free Trial Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only 3.11 2.79 1.73 2.24 2.70

Competitive Comparison of Marsh & McLennan's Debt-to-EBITDA

For the Insurance Brokers subindustry, Marsh & McLennan's Debt-to-EBITDA, along with its competitors' market caps and Debt-to-EBITDA data, can be viewed below:

* Competitive companies are chosen from companies within the same industry, with headquarter located in same country, with closest market capitalization; x-axis shows the market cap, and y-axis shows the term value; the bigger the dot, the larger the market cap. Note that "N/A" values will not show up in the chart.


Marsh & McLennan's Debt-to-EBITDA Distribution in the Insurance Industry

For the Insurance industry and Financial Services sector, Marsh & McLennan's Debt-to-EBITDA distribution charts can be found below:

* The bar in red indicates where Marsh & McLennan's Debt-to-EBITDA falls into.



Marsh & McLennan Debt-to-EBITDA Calculation

Debt-to-EBITDA measures a company's ability to pay off its debt.

Marsh & McLennan's Debt-to-EBITDA for the fiscal year that ended in Dec. 2023 is calculated as

Debt-to-EBITDA=Total Debt / EBITDA
=(Short-Term Debt & Capital Lease Obligation + Long-Term Debt & Capital Lease Obligation) / EBITDA
=(1770.727 + 12384.085) / 5792.689
=2.44

Marsh & McLennan's annualized Debt-to-EBITDA for the quarter that ended in Sep. 2024 is calculated as

Debt-to-EBITDA=Total Debt / EBITDA
=(Short-Term Debt & Capital Lease Obligation + Long-Term Debt & Capital Lease Obligation) / EBITDA
=(748.731 + 12567.148) / 4933.876
=2.70

* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.

In the calculation of annual Debt-to-EBITDA, the EBITDA of the last fiscal year is used. In calculating the annualized quarterly data, the EBITDA data used here is four times the quarterly (Sep. 2024) EBITDA data.


Marsh & McLennan  (STU:MSN) Debt-to-EBITDA Explanation

In the calculation of Debt-to-EBITDA, we use the total of Short-Term Debt & Capital Lease Obligation and Long-Term Debt & Capital Lease Obligation divided by EBITDA. In some calculations, Total Liabilities is used to for calculation.


Be Aware

A high Debt-to-EBITDA ratio generally means that a company may spend more time to paying off its debt.

According to Joel Tillinghast's BIG MONEY THINKS SMALL: Biases, Blind Spots, and Smarter Investing, a ratio of Debt-to-EBITDA exceeding four is usually considered scary unless tangible assets cover the debt.


Marsh & McLennan Debt-to-EBITDA Related Terms

Thank you for viewing the detailed overview of Marsh & McLennan's Debt-to-EBITDA provided by GuruFocus.com. Please click on the following links to see related term pages.


Marsh & McLennan Business Description

Address
1166 Avenue of the Americas, New York, NY, USA, 10036-2774
Marsh McLennan is a professional services firm that provides advice and solutions in the areas of risk, strategy, and human capital. The company operates through two main segments: risk and insurance services and consulting. In risk and insurance services, the firm offers services via Marsh (an insurance broker) and Guy Carpenter (a risk and reinsurance specialist). The consulting division comprises Mercer (a provider of human resource services) and Oliver Wyman (a management and economic consultancy). About half of its revenue is generated outside the US.

Marsh & McLennan Headlines

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