Insurance Analytics:
Going Beyond Risk
the front end of their businesses that is applied elsewhere, growth
and profitability would dramatically improve.
Insurers that
apply analytics
across the
customer
lifecycle will
see growth and
profitability.
Customer
& Agent
Acquisition
By
Scott
Staples
The global insurance industry faces unique challenges with ever-increasing regulatory pressures, new product in- novation, controlling operating costs and sustaining growth. Intelligent deci- sion-making becomes imperative to fac- ing challenging situations. The only substantial factor that can best support decision-making is data. Data analysis (analytics) provides organizations with
a framework for decision-making, solving complex business prob-
lems, improving performance, encouraging innovation, and an-
ticipating and planning for change while mitigating and balancing
risk. In order to sustain and grow against the intensifying com-
petition, the best choice for companies is analytics.
Customer
Management
Claims
Servicing &
Management
The good news is that most insurers have an abundance of cus-
tomer and marketing data across their organizations, but they
also have not leveraged its full potential. One of the prime areas
where insurers can benefit from more robust predictive models
is in customer behavior. Analytics can increase the lifetime value
of the customer manifold, streamline new customer acquisitions
and predict attrition of existing customers. Behavior scores aid in
proper product mapping to target customers in order to optimize
various marketing and product enhancement efforts. When
it comes to deriving insights about customers, data
(and how it is collected and organized) is vital.
Customer behavior scoring models that use the
power of statistics to leverage internal accounts re-
ceivables, business demographics, invoice specific
details, collection performance and other inter-
nally collected data have been found to be effec-
tive in identifying and managing risk. Models built
exclusively for existing customers that are primarily
based on actual performance are much more pow-
erful predictors of existing customers’ future per-
formance than models based merely on external
bureau data only. Behavior models are empiri-
cally derived and validated, using advanced mul-
tivariate statistical techniques to determine what
information is relevant, and how important it is to
solve the client’s business problem.
Many insurers still encounter the dilemma of how
to optimally apply analytics in their companies to unlock
customers’ potential. Most only have a vague notion about
the business areas or applications that could stand to benefit.
Second, most don’t know how to get started: whom to hire, how
to organize the project or how to architect the environment. All
these initial hiccups will be sorted once they are able to track cus-
tomer behavior and properly segment those customers. Continu-
ous monitoring across the entire customer lifecycle is necessary to
translate data into business insights and informed actions.
Insurers need to be more informed on how to collect and organize
data, and use it optimally to derive maximum benefit. Introducing
a culture of analytics to an organization and applying it across the
customer lifecycle can be a major differentiator for an insurance com-
pany. Companies that embrace this and put it into action will reap the
rewards.
Underwriting
Scott Staples is co-founder and president, Americas,
of Mind Tree, Warren, N. J. Graphic courtesy of Mind Tree.
