Wealth advisors used to succeed by making insightful lunch
conversation, being fun on the golf course and winning referrals.
These days, effectively leveraging big data is a better bet for
The growing hoard of wealth invested with robo-advisor platforms
is forcing advisers to change how they operate. By the end of
2017, $160 billion of assets will be invested in digital advice
platforms, up from $65 billion a year ago, according to research
by Aite Group and Broadridge. That number will
swell to $400
billion by the end of 2018.
Competition from these low-priced services and the trend of
replacing mutual funds with lower-priced ETFs, is compressing
fees to such an extent that advisers will need to add more
clients in order to generate the same fees.
Using data will help advisers get there. Just as Amazon can
harness data to predict what you will shop for and data helps
Netflix predict which TV series you’ll want to watch, advisers
today can leverage a huge reservoir of data to reveal everything
from what’s going on in a client’s personal and professional life
to how they want to communicate about their money decisions.
Artificial intelligence capabilities can filter and analyze data
to help advisers grow the assets being managed for existing
clients, and also market to new clients in a more targeted way.
AI programs can crunch an incredible amount of information about
existing clients to find which clients have more assets held in
other accounts and are the ones that advisers should pursue.
Broadridge research reveals that as many as one-third of all
clients fall into this category.
For marketing to new clients, data can be used to develop
marketing campaigns targeting specific sub-segments based on
demographics and psychographic information. Firms will be able to
target granular subsectors — pediatricians that own their own
medical practice in Connecticut, for example. Serving specific
groups will make referrals even more effective because a firm can
build a reputation for helping meet the needs of a specific
These methods have already been used to great effect by the
credit card industry. For example, Capital
One uses analytics of
consumer spending patterns to introduce credit cards that meet
specific customer needs. That approach has helped it become
the tenth-largest bank
in the United States.
In the future, cutting edge applications will be able to generate
recommendations from lists of available investments and products,
market events and financial plans of individual customers. Such
technology might one day be able to read the facial expressions
of a client during video meetings to reveal their unspoken
opinions about certain investment recommendations.
Getting the most from technology will be crucial because 41% of
Millennials want technology-enabled financial planning tools,
according to a
ThoughtLab survey. Just like in the credit
card business, the firms that succeed and grow in this new
environment are the ones that make the best use of data.
Steve Scruton is President at
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