Predictive analytics, enabled by machine learning, make persona marketing an achievable best practice using behavioral information.

1. Insight
W
hile big data and analytics have
long been used to ensure efficient
premium pricing,the continuing
advancement of technology is lending
itself well to more varied uses.Analytics
is largely responsible for progress in this
area,while analytic tools are evolving from
prepared data models and data scientists
to machine learning and predictive
analytics.As a result,insurers have more
options to understand and use behavioral
information to minimize risk factors.
Predictive analytics is where business
value is realized;machine learning is
accelerating its adoption and functionality.
The fact that machine learning can begin
with a historical data set or start interpreting
almost immediately via anomaly detection
eliminates barriers such as:
• Cost.The ability to run multiple scenarios
rather than a more limited set enables
continuous fine-tuning of results in real time.
• Resource limitations.Machine
learning significantly decreases the need
to find and hire data scientists.
• Single thread use cases.Multiple
models can now be used simultaneously
across silos.
As a result,predictive analytics are no
longer limited to the actuarial department.
Machine learning allows any business unit or
corporate function to optimize their value proposition.
Usage-based insurance is one increasingly
commonplace way of using data analytics to monitor
driving behavior and adjust auto insurance premiums.
While UBI has increased customer satisfaction and
retention,drivers who feel they would be penalized
if they adopted UBI have stayed clear of voluntary
participation.Therefore,behavior analysis and
modification become nonstarters.
In these scenarios,personal privacy becomes an
obstacle to adoption and a challenge in selling to a market
of one.By obfuscating personal data from
the specific individual,machine learning and
predictive analytics can use data grouping to
simulate market-of-one pricing without the
associated personal privacy concerns.
The positive impact of machine
learning and predictive analytics on usage-
based insurance can be extrapolated
to other insurance industry situations.
Marketing,for example,can be optimized
using behavioral information to both
better understand your customer base
and to predict the most likely to succeed
(least risky) marketing programs.This is
accomplished via persona marketing—
marketing to fictional,generalized
representations of your ideal customers.
According to a HubSpot marketing blog,
“personas help us all—in marketing,sales,
product and services—internalize the ideal
customer we’re trying to attract,and relate to
our customers as real humans.Having a deep
understanding of your buyer persona(s) is
critical to driving content creation,product
development,sales follow-up,and really
anything that relates to customer acquisition
and retention.”Predictive analytics,enabled
by machine learning,make persona
marketing an achievable best practice using
behavioral information.
Fraud detection is another insurance industry
use case where risk management is enhanced from
behavioral information.Acts of fraud and their causes
can be more quickly recognized or prevented using
patterns of recognition.Machine learning can then
help identify implementable deterrents based upon
this behavioral information.Continuous learning
increases effectiveness,which decreases fraud risk
exposure in both financial and time metrics.
Carriers will continue to benefit from the use
of predictive analytics,behavioral information for
effectiveness and machine learning for continuous
improvement.The concepts,techniques and tools
are there;all that remains is for insurers to justify an
innovation investment to get started. BR
By
Gates
Ouimette
Predictive
analytics,
enabled by
machine learning,
make persona
marketing an
achievable best
practice using
behavioral
information.
Technology
On Good Behavior
Carriers are turning to predictive analytics and machine learning
to better understand behavioral information in minimizing risks.
Best’s Review columnist Gates Ouimette is founder and principal of
ITconnecter. He can be reached at gateso@itconnecter.com.
Best’s Review • february 2017 • reprint
Copyright © 2017 by A.M. Best Company, Inc. All Rights Reserved. Reprinted with Permission. www.ambest.com
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BEST’S REVIEW
www.bestreview.com February 2017