There has never been a better time
for small and mid-tier insurance
carriers to embrace cloud-based analytics strategies to drive innovation
and business growth. Today’s cloud
analytics offerings and flexible cost
models put affordable, robust big
data analytics capabilities—and the
ability to innovate easily—within the
grasp of even small companies with
limited IT budgets. In fact, cloud
offerings have made robust data analytics capabilities so affordable that
carriers who choose not to exploit
cloud-based analytics offerings could be putting themselves at risk.
Early adopters of big data analytics were the large carriers who
successfully used analytics to gain competitive advantage. Recent
research shows the most innovative companies use analytics—
specifically predictive analytics—in pricing and rating, underwriting,
and in reserving, and in claims and marketing. But many early
adopters paid a high price for these innovations, especially those
adopters who chose to implement on-premises big-data analytics
solutions. So it is not surprising that many small and mid-tier
insurers chose not to be early adopters because they considered investing in big data analytics strategies to be too risky and expensive.
The cloud has been a game changer in the big data landscape.
The pay-per-use cost models of cloud-based analytics, including
platform as a service, software as a service, and data as a service
allow companies to invest selectively in targeted areas to gain value
and scale up as needed without a major up-front investment.
Analytics Platform as a Service provides the infrastructure to
create an analytics application in the cloud. These infrastructures
can be spun up and down quickly—in minutes, not weeks. The
pay-per-use pricing models from some platform as a service vendors allow companies to “rent” these infrastructures for the amount
of time needed, by the minute, hour or day. An insurer could use
this model to temporarily land and store a massive data set about
market demographics they want to explore for potential market
analysis value to increase their homeowners’ book of business.
Analytics Software as a Service provides analytics software—
such as predictive modeling or data visualization software—in
the cloud. Many vendors allow companies to pay just for the time
the software is used or in some cases for free. Insurers can use this
service to affordably develop compelling data visualizations to
guide decisions on an as-needed basis, for example, to predict the
probability of and project losses from a future natural disaster to
inform an underwriting policy decision.
Analytics Data as a Service provides access to data in the cloud
to combine with internal corporate data to identify patterns or
discover new market potential. These cloud offerings can be pur-
chased for single use or for longer-term analytics needs. For exam-
ple, insurers could purchase a one-time query into a cloud dataset
offered by a major data aggregator, thus tapping into hundreds of
individual external data sets to combine with internal system data
to feed a predictive model that could help detect claims fraud.
Carriers can choose to use any of these as a service options as
needed in the public cloud, in a private cloud behind corporate
firewalls or in a hybrid cloud environment that combines both
public and private components. Gartner projects that through
2020, the most common use of cloud services will be a hybrid
model combining on-premises and external cloud services.
This scenario from Amazon’s CTO Werner Vogels illustrates
the game-changing nature of cloud analytics:
“In the past, analytics within an organization was the pinnacle
of old style IT: a centralized data warehouse running on specialized
hardware. In the modern enterprise this scenario is not acceptable.
Analytics plays a crucial role in helping business units become
more agile and move faster to respond to the needs of the business
and build products customers really want. But they are still bogged
down by this centralized, oversubscribed, old style data warehouse
model. Cloud-based analytics change this completely. A business
unit can now go out and create their own data warehouse in the
cloud of a size and speed that exactly matches what they need and
are willing to pay for.”
Small and mid-tier insurance carriers can benefit from learning
more about the wealth of cloud analytics offerings available today
in each of these as a service analytics models and then selectively
integrate these offerings into their business and IT strategies. In
some cases, companies that embrace cloud analytics as a service
now may be able to affordably and quickly implement integrated
predictive models that simultaneously drive innovations in pricing
and rating, underwriting, and in reserving, claims and marketing.
They could even leapfrog over much larger competitors that may
be limited by their analytics solutions due to vendor lock-in or
technical debt—gaining that competitive advantage. ITA
Cynthia Walker is director of the Data Analytics Center of
Excellence at Salient Federal Solutions.
Cloud Reaches the Mid-tier
Small and mid-tier carriers can’t afford to put off adoption of cloud-based
analytics strategies.
Cynthia Walker
