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SmartData Collective > Big Data > 7 Ways Big Data Is Essential For Life Insurance Settlements
Big DataExclusive

7 Ways Big Data Is Essential For Life Insurance Settlements

Ryan Kh
Ryan Kh
7 Min Read
life insurance settlement data
Shutterstock Licensed Photo - By Panchenko Vladimir
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The life insurance industry will soon undergo a dramatic transformation in response to advances in big data. A growing number of digital startups are starting to emphasize the impact of big data in this antiquated business. A number of insurance executives have been reluctant to embrace the changes of big data. One study found that 74% of respondents felt that the insurance industry had done an inadequate job addressing the need for big data. However, a growing number of insurers are starting to appreciate the need. One area that life insurance companies can utilize big data in is with settlements.

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Several Ways Big Data is Helping with Life SettlementsBig data is the key to helping with life insurance settlements

Several Ways Big Data is Helping with Life Settlements

There are many reasons why life settlements have become more popular with consumers in recent years. These settlements have become more commonplace as a growing number of life insurance policy owners decide that they no longer need insurance coverage. Big data is assisting with many of these issues. According to a report by Inside Big Data, some of the factors that have contributed to this trend and the ways big data can be beneficial include:

  • Rising Divorce Rates ? when a couple divorces, life insurance often becomes unnecessary for one ex-spouse to carry on the other. In these instances, the policy can be sold to a settlement company for far more than the spouse would receive if they simply surrendered the coverage. They can then use the proceeds from the life settlement to pay for legal fees and other expenses related to the divorce instead of having to raid their own savings accounts. See this article on how to cash in a life insurance policy for more information. Big data helps insurers predict divorce rates and assign resources to manage the growing number of divorcing couples that need help.
  • Coverage is No Longer Needed ? Older seniors who carry large life insurance policies may eventually exhaust their need for this coverage. For example, a husband who carries coverage on his wife may eventually reach the point financially where the death benefit protection is no longer needed in order to provide for the wife after the husband is gone. The policy can then be sold and invested in something else or else used to pay off debt such as a mortgage. Big data helps insurers set premiums for people that are most likely to terminate their policy by choice.
  • Cost of Premiums Becomes Unaffordable ? In some cases, a life insurance policy can become unaffordable if the policy owner retires or experiences a drop in income. A life settlement can then be used to replace the policy with a cheaper one that the policy owner can afford. Big data helps insurers set premiums to avoid losing customers, as well as manage plans that are most likely to be terminated.
  • Increased Public Awareness ? Life settlements have come a long way from the unwieldy viatical settlements that were offered back in the 1980s. This transaction is now much more regulated and organized than it used to be, with a number of viators and settlement companies offering complete turnkey packages to purchase life policies. Many investors have come to see the value in purchasing smaller policies with face amounts of $500,000 or less and are developing streamlined processes that make buying and managing these policies simpler and more affordable. About 42 states now have legislation on the books to regulate life settlements, with 6 states having fully implemented them. The National Conference of Insurance Legislators now requires insurance companies to notify older policy owners that life settlements are a viable option instead of surrendering their policies or letting them lapse.
  • Giving to Charity ? Many life insurance policy holders who would like to make cash gifts to friends, family or a charitable organization can use their cash value policies as a source of funds with which to do so. In many cases, these policy owners can receive as much as eight times the amount that they would get if they simply surrendered their policy. This can substantially leverage the amount of money that they can provide to the recipient. Big data helps insurers find policyholders that are most likely to donate to charity.
  • An Alternative Form of Investment ? Investors who purchase life insurance policies in a life settlement can receive a rate of return that may outperform more traditional forms of investments such as stocks, bonds or mutual funds. This type of investment also doesn?t correlate with the stock and bond markets, so they can provide an important measure of diversification. A life settlement can also be used to fund other types of alternative investments, such as managed futures funds or private equity.
  • Paying Off Mortgages and Other Debts ? if a policy owner has high-interest debt such as credit card debt or a personal loan, they can sell their policy and use the proceeds to pay off this debt and escape the high interest rates that they are paying.

All of these factors have combined to make life settlements a viable option for policy owners who are looking for a way to free up some cash. These settlements provide a substantial benefit for older policy owners who may not have access to other funds. Consult your financial advisor for more information on life settlements and whether they may be right for you.

Big data is the key to helping with life insurance settlements

Consumers in the life insurance industry have long been plagued by a number of issues. Fortunately, new solutions with big data are helping them address these problems. Big data could finally be the solution to life insurance settlements.

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ByRyan Kh
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Ryan Kh is an experienced blogger, digital content & social marketer. Founder of Catalyst For Business and contributor to search giants like Yahoo Finance, MSN. He is passionate about covering topics like big data, business intelligence, startups & entrepreneurship. Email: ryankh14@icloud.com

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