Decoding your clients

George Orwell wrote that “At fifty, every man has the face he deserves.” The expression may have surprising applications to financial planning.

Wealth management is about predicting the future. This is even more true of insurance, where mortality tables — more commonly called life tables now — have been used for centuries to determine how long someone will live. Advances in genetics, medicine and artificial intelligence (AI) are creating new possibilities for forecasting longevity on a more personal level.

S. Jay Olshansky, a professor at the University of Illinois at Chicago’s School of Public Health, says the problem with traditional methods of measuring lifespan is that no person is average.

“The information that comes from these tables is for an average individual in a population,” he says. “The variation in longevity and health that you can expect in a population varies dramatically by the personal attributes that the individual has — those that are inherited and those that are acquired during the course of life.”

Olshansky and others are offering methods to track both types of attributes in an effort to more accurately predict how long someone will live. As average lifespans extend, a common concern for clients is running out of money. Being able to forecast the number of healthy years a client is expected to live could impact various aspects of their financial plans, from the level of investment risk to insurance needs to timing pension draw-downs.

“The big issue we’re all trying to figure out is [whether] there are mortality predictors,” says Karen Cutler, vice-president and chief underwriter at Manulife.

A technique known as “face age” is one of a number of new methods, along with genetic testing and tracking family history, that could be incorporated into financial planning as advisors seek to predict longevity with more precision. How useful are these tools, and how might they be adopted?

Biological age versus chronological age

If not a window to the soul, a person’s face is becoming a reliable biomarker indicating the rate at which they’re aging, Olshansky says.

“The children of centenarians throughout their lives have always looked 10, 20, sometimes 30 years younger than their chronological age,” he says. “We think this is happening because, biologically, they’re aging at a slower rate. So while somebody may chronologically be 60 or 70 years old, biologically they might be 30 or 40. And we’re picking up this signal from the face.”

Olshansky’s Lapetus Solutions offers a facial analytics tool that scans photographs, examining hundreds of regions on the face to provide estimates for a person’s lifespan and the number of healthy years they’re expected to live.

For now, it’s one of several signals Olshansky says advisors can use to predict longevity and enhance financial planning.

“While we can’t yet quantify the exact effect of the difference of face age on longevity, we’re approaching the point where we’re going to be able to do so,” he says. “For right now, if we can pick up on enough signals, like late age at menopause, young face age and family history of exceptional longevity, you’re getting some signals to indicate these individuals may [live long lives].“

To illustrate how those signals could impact financial planning, Olshansky uses the example of a couple in their early 70s who took a 23andMe genetic test. Actuarial tables would say the wife is expected to outlive the husband by about three years. The husband has a family history of cardiovascular disease and the genetic test shows he doesn’t carry a gene associated with longevity. The wife has that gene, as well as one associated with a lower risk of developing Alzheimer’s. She also reached menopause at a late age and has a young-looking face.

These factors suggest the roughly three-year difference in lifespan from the actuarial table could be much larger. “This husband and wife team are on completely different trajectories, but their advisor was completely unaware,” Olshansky says. “Imagine how you would plan differently if you had this information versus not having it.”

The situation would be different for someone carrying the gene associated with longevity as well as the one associated with late-onset Alzheimer’s. A client in that situation may be advised to buy long-term care insurance due to the higher probability of living longer in an incapacitated state, he says.

Genetic tests are a controversial tool. Canadian legislation passed in 2017 prevents insurance companies from asking for test results from applicants (see “The rules for insurance and genetic testing”).

Dr. Carolyn McClanahan, a former physician who’s director of financial planning at Life Planning Partners in Jacksonville, Fla., describes longevity in financial planning as “the holy grail.” But she’s not convinced that genetic testing will bring advisors any closer to it.

“First off, it’s an inexact science. There are so many variables, and to try to hook your longevity or life expectancy on some test, to me, is crazy,” she says.

“The second thing is, you don’t know when you’re going to get hit by a car. We need to focus on making certain that people have a good life now. If you’re not, you’re doing it wrong, because you don’t know if you’re going to have a tomorrow — even with genetic testing.”

McClanahan says a genetic test’s usefulness is limited, as many diseases are influenced by multiple genes. The test for late-onset Alzheimer’s disease has low predictive value, she says: those who test positive for the gene variant won’t necessarily get the disease, just as testing negative doesn’t mean a person is in the clear. The Alzheimer Society of Canada advises against testing for the common sporadic form of the disease as “no reliable genetic test exists.”

Dr. Samir Sinha, director of geriatrics at Sinai Health System in Toronto, says biomarkers can be useful in predicting certain diseases but not others.

“The biological testing that’s done, at least in Canada right now, is for things that are pretty black and white: Do you have this or don’t you have this?” says Sinha, who served as the expert lead on the Ontario government’s seniors strategy in 2012 and is co-chair of the advisory board for Ryerson University’s National Institute on Ageing.

Certain genes associated with breast cancer are “highly predictive,” he says, whereas the gene associated with Alzheimer’s is less so. Significant family history of a specific illness can also be a strong signal.

The technology exists to test for the presence or absence of something — whether a person has a biomarker or not, Sinha says. “The problem is we don’t know what to do with the answer. We don’t know what the answers mean. I can’t tell you with any certainty whether you have that disease.”

The science might evolve to the point where a financial planner recommends clients get tested for certain diseases, he says; for now, he’s not convinced of the benefits.

McClanahan prefers to ask clients about their health and apply their answers to financial planning. She starts with a life expectancy of 100. If the client’s finances are fine for that lifespan, she doesn’t go into greater detail.

“If, however, it looks like they’re going to be struggling to have enough, that’s when it’s important to look at their health and look at their life expectancy,” she says. “If you have a 350-pound diabetic who smokes, you shouldn’t be planning for that person to live to age 100.”

In such cases, she adapts their finances accordingly and encourages them to adopt healthier behaviours.

Interpreting the family tree

Lyle Wolberg, partner and senior financial life advisor at Telemus Financial Life Management in Detroit, Mich., uses a tool that helps clients track their family health history for financial planning purposes. Rather than relying on testing, the tool called Genivity builds a family health tree based on information gathered by the client or a close relative who acts as the family administrator.

The platform helps clients discover health facts that could impact their financial plan, Wolberg says. If a client learns about cases of a specific illness, for example, Wolberg may recommend purchasing insurance. “People typically don’t want to buy insurance unless there’s an illustrated need for it,” he says. “There are opportunities to show how it could be used as a leveraging technique because you’re still insurable. Once you’re not insurable, it’s off the board. You can’t utilize that tool for financial planning.”

On the other hand, if the family history is exceptionally healthy, he may adjust a client’s asset allocation. “You need to be a little bit more aggressive,” he says. “Because the timeframe is longer, the risk is not so much short term — it’s outliving their wealth and their money. They need to keep pace with inflation for longer periods.”

Wolberg says Genivity is used to tweak financial plans; its findings aren’t taken as gospel. “As a fiduciary you have to be a little bit more conservative,” he says.

The service has proven useful to his practice in another way. He says health discussions have strengthened his relationship with spouses who are less involved in financial decisions, and introduced younger family members to the firm.

“Part of an advisor’s challenge is the transfer of wealth from generation to generation,” he says. “I think we’re always looking for ways to get to know other generations or family members. Once that person has inherited the wealth, it’s typically too late to try to retain that relationship.”

The client experience

Karen Cutler, Manulife’s chief underwriter, says a number of players are experimenting with ways to provide information that insurance companies currently get from questionnaires and tests. These range from wearables that track a customer’s fitness to innovations such as Olshansky’s face-age tool.

“Are the mortality predictors that they’re developing actually going to be better than what we do today through the question and answer? That’s the big challenge,” she says.

“They’re interesting tools. I think at some point we’ll be using something along those lines. We just haven’t come across anything yet where we’ve been able to prove that we’re going to get a benefit, or that our current approach can be replaced. That’s not to say it won’t happen — I believe it will happen.”

Part of the decision about whether to adopt new practices will come down to the customer experience. Providing a less invasive process to customers would be welcomed, but privacy concerns are paramount.

Last summer, a consumer app with functions similar to Olshansky’s, called FaceApp, became popular for a few weeks before the Russian-owned company’s sketchy terms of service were widely circulated, spooking users. Cutler says she’s not sure customers are ready to send photos for insurance companies to scrutinize.

Genetic tests, while out of play for now in insurance, are even more sensitive.

There’s also the question of how much a client actually wants to know. The average person may be seeking reassurance that they won’t run out of money in retirement — not a crystal ball prophesying their death.

Olshansky says there could be a mechanism that allows advisors to access genetic or other information for planning purposes without going into detail about the results with the client.

“Not everybody wants to know how long they’re likely to live,” he says. “We need to be very careful to make sure we’re delivering the information in a way that is exactly the way in which people want to receive it. Most people are anxious to get this genetic information. Others don’t want to see it at all. They just want to know what they should be doing.”

David Brown, partner at Al G. Brown and Associates in Toronto, says the industry may not be ready to enter the business of predicting how long clients have left.

“In the world of financial planning, we’re very concerned with people running out of money. We don’t want to second-guess when they’re going to drop off the planet because, if we’re wrong, it’s a bad thing. The chances are that we’re going to be wrong because no one really knows anyone’s individual life expectancy,” he says.

Brown gives the example of his father, the firm’s namesake, who died at the age of 96 and worked into his final year. Al G. Brown had a heart attack in his forties. Averaging the life expectancy for a group of men who had heart attacks at a young age would be a lot younger than 96, David Brown says.

“I’m very concerned with financial plans that predict that you’re going to run out of money at a particular point in time. I believe financial planning has to cover various types of risks, and one of the risks is longevity risk.”

The rules for insurance and genetic testing

Parliament passed the Genetic Non-Discrimination Act in 2017, preventing employers, insurance companies and others from asking people to take genetic tests or to disclose genetic test results. However, the Liberal government and several provinces said the law may infringe on provinces’ jurisdiction over health insurance.

The insurance industry, worried the law would undermine the balance of information between customers and insurers, resulting in higher premiums, lobbied against the bill.

The Quebec Court of Appeal ruled the law was unconstitutional late last year. The Supreme Court of Canada heard the case Oct. 10.

What do our genes tell us about financial behaviour?

While scientists and corporations invest heavily to research the relationship between genes and aging, researchers in the field of neuroeconomics are conducting experiments to determine the link between genes and financial behaviour.

Scientists at Northwestern University found that variants of two genes that regulate the transmission of dopamine and serotonin play a significant role in risk-taking when it comes to investments. The paper, published in 2009, found that risk-taking varied by roughly 25% based on which gene variant an individual carried.

In 2009, academics from New York University, the University of Cambridge and the Stockholm School of Economics also found that genes account for roughly one-quarter of variation in portfolio risk. The researchers matched portfolio choices made after pension reform in Sweden with the country’s twin registry to show what role genes play in financial decision-making.

More recently, a researcher from the University of Washington’s Foster School of Business also used the Swedish twin registry, as well as the Swedish government’s record of citizens’ financial transactions required under its former wealth tax. Foster’s Stephan Siegel and Henrik Cronqvist from the China Europe International Business School compared the records for identical twins, who share 100% of their DNA, and fraternal twins, who share 50%, to isolate the genetic component of financial behaviour.

They found that roughly 30% of the variation between individuals is attributable to genetics—more than the combined factors of age, gender, education, wealth, home ownership and parenting. At least half of the variation between people, they said, is shaped by individual experiences.

What does this mean for financial planning? Probably nothing, for now. It could be some time before gene variants make their way into know-your-client forms. But it’s possible that a decoded genome could eventually be used. Siegel believes asset management will increasingly rely on data and genetics to the point where client profiles are developed through a combination of transaction history and genetic information.

Other uses for face-aging technology

The popularity of FaceApp, a tool that allows people to age a selfie to show how they’ll look as a senior, hints at another potential use for facial analytics applications. Studies have shown that people who see aged versions of themselves feel more empathy toward their future selves and become more willing to save for retirement.