Investing in life: numbers about life insurance


Pavel Prikhodko, Ph.D. Machine Learning

A recent survey examined the major reasons for purchasing life insurance in the United States. During the survey, respondents were asked to indicate their reasons for buying life insurance. The majority of the respondents (85 percent) said that one of their primary reasons for purchasing a life insurance policy was to cover burial and other final expenses. About 67 percent of the respondents stated that a major reason was to help replace the lost wages/income of a wage earner, while 63 percent mentioned that transferring wealth or leaving an inheritance was an important reason for their life insurance policy.

We’ve looked at the reasons that cause Americans to buy life insurance, but what reasons cause Americans not to purchase it? First of all, it is too expensive; 66 percent of respondents in 2017 cited cost as a factor in their decision not to purchase life insurance. The same percentage of respondents admitted that they did not buy life insurance because they had other financial priorities. Additionally, 54 percent of people said that they have as much as they need.


If we look at the distribution of life insurance ownership in the U.S. in 2018, we see that the majority of Americans had a life insurance policy; 60 percent of Americans owned life insurance while 40 percent did not.


Next, let’s analyze the leading life insurance companies in the United States in terms of market capitalization. As of February 2016, the largest life insurance company by market capitalization was MetLife. MetLife (which was founded in 1868) is one of the largest global providers of insurance and employee benefits programs; the company’s market capitalization amounted to $49.22 billion in 2016.

Another major company, Prudential Financial, came in second place with a market capitalization of $31.03 billion. Aflac took third place in terms of market capitalization, reaching $24.73 billion.


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About Pavel Prikhodko


Pavel Prikhodko, Ph.D. Machine Learning

Pavel has worked for many years as a researcher and developer on a wide range of applications (varying from mechanics and manufacturing to social data, finance and advertising), building predictive systems and trying to find stories that data can tell.

In his free time, he enjoys being with his family.

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