Morningstar Magazine - June/July 2017 - 52

Spotlight: The Future of Investing

Demographics

Gender, education, geography, marital status,
and life expectancy should be used to help tailor
advice to the individual.
Human advisors are likely to factor demographics into their recommendations. For example,
advisors will take into account geographic
location in their selection and recommendation
of municipal bonds, which are double taxexempt. They likely will factor in family health
when planning for portfolio longevity and
recommending annuities and other insurance.
Today, robo-advisors do little to consider
demographics. But "can it be done?" Of course!
Demographic information is rather easy to
collect; it's what you do with it that counts. Take
Ellevest, a robo-advisor focused on women.
(Morningstar is an investor in Ellevest.) Ellevest
believes investing can be tailored to the unique
needs of women to create a better experience with
better outcomes. Ellevest takes into account
a woman's lifetime salary curve, including more
career breaks and a gender pay gap, in addition
to longer lifespan.
Once robos expand their investment menu,
difficult-to-compare annuities and municipal bonds
(or bond funds) can be matched and priced based
on demographics. Robo dating services have
become commonplace for matchmaking based on
demographics, preferences, and unique
characteristics, so taking this to the financial realm
really isn't much different. In fact, it's inevitable.

up mapping the user to a model asset allocation
ranging from conservative to aggressive risk.
Say, however, one person makes $200,000 per
year and another makes $35,000, but both
complete a questionnaire that maps them to the
same conservative portfolio. If both are
the same age, it is clear that these two people
have different financial capacities to take on
risk, so their portfolio advice should be different.
Whether through the formation of a financial plan
or account aggregation of held-away assets,
human or machine can compare assets, liabilities,
and earning power to model an individual's
capacity to take on risk.
Risk-tolerance questionnaires are also problematic
because they represent an individual's stated risk,
when we know that people often say and do
different things. Psychometric testing can be used
to observe risk tolerance. UBS UBS is rolling out
a robo-advice service in Europe that, the company
says, will give clients a series of visual tests
designed to determine how risk-averse they really
are. Investors will then receive a signed document
offering personal advice.
Richard Peterson, chief executive officer of
MarketPsych, says such tests "allow us to estimate
the fundamental patterns and personal
tendencies in risk assessment, emotional coping
techniques and ultimately investment decisionmaking. Because of innate biases in how
we reflect on our own behavior, [an investment
platform] can ascertain a level of risk assessment
that it can't from self-reporting."

Risk Profile

The measurement of an individual's willingness
to take risk should be informed by his or her
tolerance and capacity for risk and the minimum
risk required to achieve an outcome.
Risk-tolerance questionnaires are insightful, but
they only paint part of an individual's risk-profile
picture. They do an adequate job assessing
a person's tolerance for risk. Often this takes the
form of a five- to seven-question survey that ends

Risk-tolerance questionnaires had their day,
but it is time to look beyond them in forming
a forward-looking risk profile of an investor.
Machines can do an excellent job of measuring
both risk capacity and psychometric-observed risk
analysis to paint a more accurate picture.
Goals

Investing is no longer focused on beating
benchmarks but achieving life goals.

Gone are the days when investment success was
measured simply by beating the S&P 500. People
want to know that wealth is there for them to
achieve their desired financial goals, such as
providing a comfortable lifestyle into retirement.
But even goals are difficult to wrap our heads
around. In fact, it's a relatively new concept.
Prior generations had pensions and Social Security
to provide for retirement, and most didn't plan
for college expenses. But today, parents send their
kids to college at an astronomical price while
also having to fund their own defined-contribution
plans. Generation X started to focus more
on life experiences than material things, while
millennials have taken that concept even further.
Financial success is now viewed through
a personalized goals-based lens, such as funding
college, a wedding, a house purchase, vacations,
and retirement.
Once again, human advisors have an advantage
here at knowing their clients. Or at least,
they should. But knowing their clients isn't enough.
People have a tremendously difficult time
forecasting their wants and needs into the future.
A 2011 Stanford study concluded that people are
reluctant to save for retirement because they don't
identify with their older self.2 After showing people
an aged computer-generated image of themselves,
"those who interacted with their virtual future
selves exhibited an increased tendency to accept
later monetary rewards over immediate ones," the
study says. In 2012, Merrill Edge put this concept
to work by launching an online magic mirror
called Face Retirement, which uses a facial-aging
algorithm and a computer's camera to show
clients what their older selves might look like.
Shane Williams, co-head of the new U.K.
robo-advisor from UBS, says that "goals-based
investing is about what makes us human."
But today's robos are still simplistic. Some services
will present a couple of paths up-front, such as
saving for retirement or general investing.
More advanced services will offer up a menu of

2 Hershfield, Hal E., Daniel G. Goldstein, William F. Sharpe, et al. 2011. "Increasing Saving Behavior Through Age-Progressed Renderings of the Future Self," Journal of Marketing Research, Vol.
XLVIII, November, pp. S23-S37.

52

Morningstar June/July 2017



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