How research in longevity could make a photo of your client’s face more important than their blood in determining life insurance underwriting.
The iPad soon could replace the vial of blood as the most accurate tool for obtaining information for life insurance underwriting.
That’s the word from a noted expert on longevity science, whose research on unlocking the secrets to why some people live much longer than others inadvertently became the foundation for a science-based method of underwriting.
Dr. S. Jay Olshansky presented his findings on longevity and how they form the basis for this new method of underwriting at the 2016 LIMRA Life Insurance Conference earlier this year. Olshansky is a professor in the School of Public Health at the University of Illinois at Chicago and research associate at the Center on Aging at the University of Chicago and at the London School of Hygiene and Tropical Medicine. His research on longevity has been published in numerous magazines, newspapers and scientific journals. In addition, he is co-author of the book The Quest for Immortality: Science at the Frontiers of Aging. Olshansky is co-founder of Lapetus Solutions, which is developing a web-based underwriting platform based on his research.
What set this method apart from traditional underwriting are its speed, its ability to obtain accurate information about the applicant’s health without the need for taking blood and urine samples, and the scope of questions asked of the applicant. Instead of ordering blood tests for the applicant, the life insurance agent is asked to take a photo of the applicant’s face and upload it to the website. And although the applicant is still asked questions about his tobacco use, height and weight, the questioning is focused more on the health and longevity of the applicant’s family members — particularly his parents and grandparents. The whole thing can be done online, preferably with a tablet, Olshansky said. With this process, he said, the underwriting process could be reduced to a matter of minutes.
The Science Behind the System
Olshansky said he hadn’t intended for his research to be applied in the life insurance industry. He said his research was focused on answering the question: why do we age and live as long as we do?
Insurers traditionally have calculated longevity and mortality based on a formula created by an actuary in 1825, Olshansky said. That formula was an assessment of the relationship between age and duration of life and mortality risk. “That formula has been used essentially forever,” he said, with some modifications such as the testing of body fluids and taking tobacco use into account.
But the science that underlies the relationship between all of these risks and duration of life has never been applied in the insurance industry directly, he said. “Insurance underwriters know that smoking is bad, so they assume it is bad for everyone. They know that obesity is bad, so they assume it is bad for everyone. The fact is that they’re not. In fact, there’s a lot going on that determines the duration of life that has actually never, ever been used in the insurance industry to assess risk.”
The Industry Shows Interest
Several years ago, Olshansky was invited by Bob Benmosche, former CEO of AIG, to discuss the future of longevity. “I gave a presentation to his people on the science of aging and why it is that we are able to predict longevity in fundamentally different ways than what the insurance industry has been using.”
Benmosche suggested Olshansky present this science to the insurance industry and describe a practical way that the industry can make use of this information.
Olshansky said he showed Benmosche a photo of a 100-year-old man and his son who was 70 years old but looked more like 50. “In the world of aging science, we have seen a consistent phenomenon,” Olshansky said. “The children of long-lived people tend to look younger throughout their lives. For example, if you’re 70 years old, you could look 50. What this means is that while these people may be chronologically 50, 60 or 70 years old, biologically they may be 10 to 20 years younger, which means their mortality risk is that of someone who is 10 or 20 years younger. Since the risk of death in humans doubles about every eight years, these are not trivial differences. A difference of eight years means that actual mortality risk is about half that of the average person your age.”
This is all basic science that had never been used in insurance underwriting before, he said.
Olshansky began working with Dr. Karl Ricanek of the University of North Carolina-Wilmington, the creator of facial analytics. Ricanek had created a computer program that does what your eyes do when you see someone’s face and determine whether they look younger or older. But the program also assesses how old that person looks relative to others their age. The two scientists began taking the information generated from that program and translating that into actual mortality risk.
Their Intent Was Research
“Our intent was to do research – not work in the insurance industry,” Olshansky recalled. That all changed when The Washington Post published an article on their research. As a result, he recalled, “We were inundated with photos that people wanted us to analyze. We received 1 million images within a month.”
Soon afterward, Olshansky and Ricanek were contacted by a number of entrepreneurs who told them their research had created something that could alter the insurance industry.
“We realized we created a program that allows us to assess risk in fundamentally different ways using the tools of aging science that allow us to tap into underlying biological factors that influence the duration of life,” Olshansky said. “None of these factors had been used or considered at all in insurance underwriting.”
For example, the questions that Olshansky’s program asks go beyond asking for information about the applicant himself. Many of the questions ask about the health and longevity of the applicant’s parents, grandparents, uncles and aunts. How long did they live? What was their cause of death? How many relatives survived to age 85 and beyond?
Another section of questioning for women deals with the age at which they reached natural menopause. “How long we live is related to the length of time when reproduction occurs,” Olshansky said. “Women who go through natural menopause late tend to live significantly longer than those who go through natural menopause early. But asking about menopause — this is not a question that is asked during insurance underwriting.
“Even if you smoked or had other harmful behavior risk factors, if you went through menopause late, you have long-lived ancestors and you look young for your age, there is a high probability you will live a long life.”
As a result of his longevity research, Olshansky said, the industry now has an ability to “identify subgroups of the population who should be considered super-preferred individuals with a very low risk of death and a high probability of long life.”
Another example of a change in the traditional way of questioning is regarding tobacco use. In the industry, he said, former smokers are considered nonsmokers if they quit more than a year ago.
“But former smokers are NOT the same as nonsmokers – they have a significantly higher mortality risk,” he said. “We would want to ask former smokers more questions: how long since you last smoked, how long were you a smoker, how much you smoked, if you live in a house with a smoker.”
The Practical Application
Olshansky and his partners constructed a computer platform that takes this knowledge of aging science and puts it in one place. The agent can take a photo using a tablet, enter the applicant’s answers to the questions, upload the applicant’s photo and get an estimate of their expected longevity. The program also gives the agent the probability of the applicant’s surviving to age 65 and the probability of their surviving beyond the projected life expectancy.
“But all the client would see is whether or not they are accepted for coverage, at what rating and what the premium would be,” he said.
Looking ahead to the future of science-based underwriting, Olshansky said that wearables can be used to capture data on an individual’s daily activities and physical patterns. “A year’s worth of data from a wearable can tell you how well you’re driving your body — your sleeping patterns, your step patterns, your blood-glucose levels — all science based,” he said. “From there, we can predict things such as what’s the age at which you’re likely to begin experiencing some frailty or needing some assistance. We can generate a healthy life expectancy as well as an overall life expectancy.”
Olshansky said he has met with 20 or 25 insurance carriers who are interested in the technology, and he estimates that the first company to begin using it could have it up and running sometime this summer.