How AI And Aging Research Can Help Life Insurance Companies? – Forbes

How AI And Aging Research Can Help Life Insurance Companies? - Forbes

Robot and dice

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If you ask a lay person on the street what life insurance is, and they’ll tell you it is a policy you buy that pays a sum of money to your family when you die. Ask them to explain how life insurance works, and they will probably tell you it is a contract between an insuring company and a policy owner. Now ask them how artificial intelligence (AI) and aging research can help life insurance firms and policy buyers make decisions with conviction, and they’ll scratch their heads and likely walk away from this conversation, or give very general answers.

And while the customers are pretty much in the dark, some of the more innovative insurance companies are building substantial internal and external capabilities in both aging research and artificial intelligence. And there are hundreds of startups with more or less credible technologies that the life insurance companies are partnering with directly or through the open innovation hubs. Some of these innovation superhubs are run by the reinsurance companies but some are run by the global insurance powerhouses such as Generali. For example, House of Insurtech Switzerland. There is a lot of progress in the field.

In this article, I suggest that the recent developments in AI and aging research are going to disrupt the traditional models of how life insurance companies operate and can help them, as well as policy owners, make better informed decisions.

Before we dive into that, however, we need to understand how life insurance really works.

Life insurance concept.

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The truth about life insurance and how it really works

In simple words, life insurance can be defined as a contract between an insurance company and a policy holder or buyer, where the insuring company promises to pay a certain amount of money in exchange for a premium, either upon the death of an insured individual or after a set time period.

Before you make the decision to purchase life insurance, you will surely have lots of questions. How much will a certain policy cost? How do various life insurance policies compare with each other? Whether you should opt for a term or whole life policy? The list goes on. Unfortunately, while you may have many questions, life insurance companies on their part have only one: How long is this person (policy holder/buyer) likely to live? After all, insurance companies need to accurately assess risk and set your premium.

So before insurance companies decide to insure you or sell you a policy, they will gather lots of information about you to determine how much they’ll charge for coverage and what amount they’ll pay to the people you name as beneficiaries in your policy contract.

Another reason life insurance companies need all of this information about you is to create underwriting standards, which is a critical step in the purchasing process when insurance companies assign applicants a classification based on various factors and determine the appropriate pricing for a life insurance policy. 

To help you understand, here’s a rundown of some of the information insurance companies gather about you (at the very least): medical history, motor vehicle records, criminal records, electronic health records, financial records, professional licenses, details about your lifestyle, and much more. Many standard life insurance products that are commonly integrated in employee benefits, annuities and other financial products the amount of this information used is usually minimal and population averages are used. However, for packages with large payouts, detailed health checkups are usually performed.

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Underwriters often consider your age, gender, as well as other data – for example if you smoke or drink – to evaluate risk. So if you like a drink or two and work at a high risk job where the chances of you getting injured or dying are higher, you may have to pay higher premiums than someone who does not drink at all and works at a library or someplace with very low risk of getting injured and dying.

The real reason life insurance companies gather information about you is to determine the policy that best fits your needs.

Once insurance companies collect all of this information, they may ask you to chose which type of insurance policy you want to buy.

Generally, there are two types of life insurance: term and permanent insurance.

A term life insurance policy provides coverage for a specific period of time, typically between 10 and 30 years. Permanent life insurance provides coverage that lasts your entire life. There are other types too, such as: Universal life insurance, variable life insurance, simplified issue life insurance, guaranteed issue life insurance, and group life insurance, among others.

Once you select the type of insurance you want to purchase, you might sign a document and think the process is now over and, in a way, you’re right. But that’s not the end of it.

Advances in medical and aging research, driven by an investment boom in longevity biotechnology, are likely to make people live long and healthy lives. This means life insurance companies will have to rethink their entire traditional model of collecting data and assessing risk.

According to data provided by the World Bank, the average global life expectancy in 2019 was 72.7 years, almost 2.3 years more than a decade ago in 2009, and nearly 5.2 years more since the turn of the century. Longer average lifespan alone may disrupt how life insurance works.

Healthier people with longer lifespans, on the other hand, will certainly shake up how life insurance companies operate.

Last year, Amazon founder Jeff Bezos was reported to have invested in a new longevity biotechnology company called Altos Labs, which hopes to prolong human life. The biotechnology company recently launched with an aim to restore cell health and to reverse disease, injury and disabilities. Altos Labs is not the only company working on healthier and longer lives, there are many other companies too.

On the investment side, many new companies emerged over the past decade and started investing in longevity that are managed by experts specializing in this specific field. The $100 million Longevity Vision Fund set up by Sergey Young, Longevity Fund by Laura Deming, LongeVC by Garry Zmudze, Formic Ventures, by Michael Antonov, BOLD Capital by Peter Diamandis, Kizoo Ventures by Michael Greve, and several others. Korify Capital recently launched a new venture fund that aims to raise up to $100 million for investments in biotech platform companies that focus on longevity and mental health. There are other firms aiming to extend heath span and lifespan. including Apollo Health Ventures, which closed a $180 million venture fund in 2021 to build biotechnology and healthtech ventures aimed at increasing human healthspan.

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Even the world’s largest intergovernmental organization, the United Nations, recently unveiled the Decade of Healthy Aging (2021-2030), which aims to improve the lives of older people.

There are countless other examples of similar investments and pledges in longevity research. We are living in a remarkable era where stakeholders from the private sector, billionaires, and governments are joining hands to ensure healthier and longer lives of all humans. All of these steps mean that life insurance companies, as we know them now, will cease to exist in the future.

However, there are certain technologies that life insurance companies can utilize and that will actually help them and people make better informed decisions with regards to buying life insurance.

Healthcare technology concept for the use of artificial intelligence in population health.

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Why AI and aging research will disrupt the life insurance market

The recent advances in machine learning and artificial intelligence, coupled with increases in computational power, have led to a lot of interest and hype in longevity biotechnology. Hundreds of data scientists and companies are taking advantage of this hype to propel research and discovery of new technologies in aging research.  

One of the major new areas in aging research are biomarkers of aging that give the true biological age of humans that may be different from their chronological age. One of the most advanced biomarkers of aging are deep aging clocks that can help researchers predict biological age as well as mortality of humans. In 2013, Steven Horvath published an article called ‘DNA methylation age of human tissues and cell types,’ in which he outlined the development of a multi-tissue predictor of age that allows for the estimation of the DNA methylation age of most tissues and cell types. He also formed an aging clock that can be used to address questions in developmental biology, cancer, and aging research.

There have been several more studies on such clocks since 2013. For example, I was part of a team in 2016 and we published a study on the first deep aging clock titled ‘Deep biomarkers of human aging: Application of deep neural networks to biomarker development.’ Since our study was published, many other aging clocks that can predict age as well as mortality rapidly entered into many industries.

While there are types of aging clocks that require expensive data such as blood tests, or even tissue tests, there are also other types of aging clocks that are very simple. These clocks can use sensor data, data from your mobile phone, and even psychological surveys, to accurately predict your psychological age. One example is a questionnaire developed by XPRIZE and Deep Longevity that uses AI to analyze a users’ answers to predict their chronological age.

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This research is rapidly propagating into the clinical practice with the advent of a new branch of medicine – longevity medicine where artificial intelligence is pretty much a central theme. Thousands of physicians around the world started studying this exciting new area, and many of the aging biomarker-enabled clinical trials and meta clinical are on the way.

Aging clocks that can accurately predict the true biological age of humans are gaining popularity across various industries because of their broad range of uses. So, how can life insurance companies use AI-based clocks in their industry? Keep reading below.

InsurTech – Insurance Technology

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Here’s how life insurance companies can benefit from AI and aging research

First and foremost, life insurance companies can use AI-based aging clocks for the underwriting process. Since these clocks are better predictors of mortality than chronological age, the biological age can be plugged into the actuarial tables to better assess the risks.

Second, aging clocks can be used for customer acquisition. People who are more aware of their biological age may be more interested in planning their future and buy life insurance products.

Third, life insurance companies can benefit from AI to develop new products. There are some cutting-edge insurance companies that are actually planning to use these clocks to develop new exciting products that can help them get new customers, retain them longer and make them more engaged. Here the term LifeHacker gets a completely different meaning!

Fourth, it is clear that there is a boom in the longevity biotechnology industry and huge progress in aging research is expected to be made in the next few years. AI-based aging clocks provide a very good entry point for the insurance companies to get into the field of aging research and actually contribute while protecting their business and innovating in science and technology.

Finding the way.

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The bottom line

Imagine a world, not so much in the distant future, where the average life expectancy exceeds 100 years. Now imagine that that 100 year lifespan does not include any diseases but is rather a healthy lifespan. Thanks to investments and research in longevity biotechnology made in the last few years, coupled with more interest from the young scientists, this idea of a 100 year healthy lifespan will soon become a reality. As better predictors of chronological and biological age enter the market, it is equally important for companies to fully take advantage of deep aging clocks simply because of their broad range of applications. This is an area where life insurance companies can use AI and aging research to make better decisions regarding risk assessment and setting premiums for new users/buyers. Now is the time to ditch the traditional models set by life insurance companies and embrace the new era led by biotechnology.