White Paper
High Value Data and Analytics:
Building a Platform for Growth
What’s hidden in your data?
Analyze, realize and optimize the possibilities.
Created by industry experts, this publication is the first
in a new LexisNexis® thought-leadership series on data
and analytics for the insurance industry.
This white paper is the first in a series that will explore how insurers can strategically
use data and analytics throughout the policy lifecycle to drive growth. Future papers
will leverage LexisNexis expertise and insight to explore the topics introduced in this
paper in more depth.
Topics
Insurance Business Environment:
• Saturated Market/Fierce Competition.
• Market Segmentation/Moving to the Next Level.
• The Vital Role of Pricing.
• Customer Servicing and Retention.
• Limited Use of External Data and Analytics.
Data and Analytics as Differentiators:
• Building on Your Foundational Data.
• The Value of Emerging Supplemental Data.
• Leveraging New Analytics Models and Services.
• Integrating Data and Analytics Enterprise-Wide.
Winning in a Saturated Market
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About the Authors
Deb Smallwood, the Founder of SMA, is highly respected throughout the
insurance industry for strategic thinking, thought provoking research,
and advisory skills. Insurers and solution providers turn to Deb for insight
and guidance on business and IT linkage, IT strategy, architecture, and
eBusiness. Those seeking an edge in today’s highly competitive world turn
to Deb to capitalize on her deep industry knowledge and experience and
her specialized understanding of distribution and underwriting automation.
Mark Breading, a Partner, is the one to turn to for provocative thought
leadership concerning insurance industry challenges, opportunities, and
technology options. He has exceptional knowledge and experience in all
aspects of Customer Centricity—CCM, CRM, customer insights, ECM, data
and analytics, and more. Both insurers and IT solution providers look to
Mark for everything from future vision to strategic key account marketing.
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Insurance Business Environment
The insurance environment for property and casualty personal lines is
highly competitive, causing insurers to seek new competitive advantages.
These advantages are built on a better understanding of customers and
risks. This whitepaper discusses the high value that data and analytics can
bring to insurers as they seek competitive differentiators in
these areas.
This section will identify five key elements of the current insurance
business environment—describing what insurers need to do to gain
competitive advantage. The next section—Data and Analytics as a
Differentiator—covers how insurers can build the capabilities needed
to be successful. The final main section—Winning in a Saturated
Market—highlights specific steps for insurers to take to get started.
Saturated Market/Fierce Competition
Property and casualty personal lines in North America are mature markets
characterized by a large number of companies fighting for market share.
The two largest lines—private passenger auto and homeowners
multi-peril—are saturated, since automobile insurance is mandatory and
homeowners insurance is required for anyone seeking a mortgage. In this
industry, growth comes by stealing share and increasing prices during hard
markets. Unfortunately, the industry is still in the midst of a soft market,
waiting for the economy to pick up steam and support rate increases. The
prospects for 2011 are uncertain and insurers are seeking ways to gain
and maintain a competitive edge and achieve growth. One way to gain a
competitive advantage is to gain a better understanding of, and capitalize
on, consumer shopping behavior. A recent study conducted by LexisNexis
reveals that over half of all consumers shop only one insurer. In addition,
the vast majority of shopping occurs between the renewal notice and the
policy end date. Insurers that target policyholders before the renewal
notice arrives have a greater chance of success.
Market Segmentation/Moving to the Next Level
Another important strategy is to employ sophisticated market
segmentation, and tailor products and sales approaches to each segment.
Insurers have been using segmentation approaches for many years, but
many continue to rely on traditional demographics for their analyses
(age, gender, race, geographic region). These basic demographics still
have value, but only allow for segmentation at a macro-level. Trumping
the competition in today’s market requires micro-segmentation—using a
deeper understanding of changing demographics and changing shopping
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One way to gain a competitive
advantage is to gain a better
understanding of, and
capitalize on, consumer
shopping behavior.
behaviors. Insurers with advanced marketing capabilities often have
hundreds or thousands of segments, rather than a handful of general
segments (e.g. Gen-Y, Baby Boomers). The key to moving to the next
level of segmentation is the availability of robust data—internal and
external—and the ability to use sophisticated analytical tools to gain
insights. This allows insurers to understand buying motivations, the
likelihood and timing of insurance shopping, and price elasticity.
The Vital Role of Pricing
The successful execution
of key competitive strategies
is, in many cases, hampered
by the availability of the right
Gaining deeper insights into customers and tailoring products and sales
to micro-segments is a good start, but insurers still need to excel in the
fundamentals of the insurance business—underwriting and pricing risks.
Insurers desire growth, but this quest for growth is not an end in itself.
The growth must be profitable—and that gets back to the basics of
understanding the risks that are underwritten, and matching the price
to the risk.
Pricing is becoming increasingly sophisticated in the insurance
industry—and the key enablers are the right data and analytics tools.
Having a more complete picture of the consumer allows insurers to more
accurately predict losses and price the risk. In addition, insurers with an
understanding of when pricing is a competitive advantage are able to
determine whether to reduce the price to acquire or retain a customer,
and what the best price should be.
Today, market leaders are leveraging many different external data sources,
and predictive analytics tools and services to segment and expand rate
structures, filter new risk appetite, and align price with risk analysis. Claim
loss histories are one example of critical external data that insurers should
acquire and analyze, especially since claim severities continue to rise and
frequencies are likely to increase as economic conditions improve.
Customer Servicing and Retention
The most profitable insurers excel at servicing the customer,
cross/up-selling, and keeping them on the books. Providing great policy
servicing, billing, and claim services requires a service-oriented culture
as a start. But even the best people are handicapped if they don’t have
the right data and customer insights when they are interacting with the
customer. The trend is for insurers to create new customer insights for
deep understanding and expansion of customer intelligence. For example,
insurers that fully leverage information in the marketplace are able to
prefill substantial portions of an application, making the process easier and
faster for customers. Similarly, prefill at the point of claim can make the
First Notice of Loss process easier and facilitate faster claims resolution.
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data and analytics
capabilities.
In addition, more information and insights about customers’ needs and
behaviors create cross-sell and up-sell opportunities. Identification of a
youthful driver in the household is one of many examples that present an
opportunity for the insurer to gain more business.
As insurers seek a new edge,
Limited Use of External Data and Analytics
some are recognizing the
Many insurers have strategies and specific plans to move market
segmentation to the next level, improve matching of price to risk, excel in
customer servicing, and increase retention. The successful execution of
these strategies in many cases is hampered by the availability of the right
data and analytics capabilities. It is well known that many insurers struggle
with data management due to the volume and complexities of their data.
Data is often isolated in departmental areas—with marketing, underwriting,
and claims having their own sets of information. Each business area may
acquire or develop point solutions along with the siloed data. Data and
decisions made in one part of the business are not necessarily easy to
access by another part of the enterprise. The external data acquired by the
insurer is brought into the company to support individual transactions and
decisions (see Figure 1).
unique value of new and
different types of external
data­—beyond the traditional
data insurers have typically
purchased.
Source: SMA 2011
Figure 1. Traditional Insurance Policy Lifecycle: Data Supports Individual
Transactions.
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Although today’s environment brings value to the specific transactions and
end-users of the data, the value is limited. Data is treated as a transactional
commodity rather than a strategic differentiator. With siloed use of
external data and services, the value is restricted. With a more holistic
view across the whole policy lifecycle and across the enterprise, the value
increases exponentially.
Successfully leveraging data
Data and Analytics as Differentiators
solid business strategy that
Insurers need to take a comprehensive view of data and services to address
the challenges and opportunities created by the insurance business
environment. Specific capabilities are required based on foundational data,
emerging supplemental data, analytics, and the integration of the three.
and analytics is based on a
requires data capture and
integration throughout the
policy lifecycle.
Building on Your Foundational Data
Insurers must address the challenges related to data and analytics if
they are to be successful in the crowded, competitive P&C personal
lines marketplace. The first step in tackling this area is to build on the
foundational data the enterprise already owns and/or uses. This comprises
both internal, proprietary data, and data purchased from external sources.
The starting point for insurers should be to inventory data currently in use.
Internal data should be assessed to determine what is available and
where it is located in the enterprise. External data should also be
inventoried—including foundational data used for underwriting such as
credit scores, motor vehicle records, and claim loss information. Insurers
should then determine what additional data to capture early in the
lifecycle—data that may not be needed for the immediate transaction but
that may be useful later. For example, capturing claims related data at the
point of underwriting can expedite claims processing and improve fraud
detection. In addition to understanding the critical internal and external
data in use, insurers should strive to maximize the value of this information.
Sometimes the same data may be purchased and used by different
departments, resulting in unnecessary expense and confusion. At other
times, insurers order data from an external provider, only to discover that
they really did not need it to support the original transaction or decision.
The use of predictive models to determine the likelihood of unnecessary
information can result in substantial savings in transactional costs
(e.g., whether to order MVRs or property inspections).
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The Value of Emerging Supplemental Data
As insurers seek a new edge, some are recognizing the unique value of
new and different types of external data—beyond the traditional data
insurers have typically purchased. This emerging supplemental data is
now available from data providers because data from many public and
private sources is now routinely digitized. Vast amounts of new data are
available to and relevant for insurers. Public records from county assessors,
county recorders, and other government entities enable firms to leverage
information such as property characteristics, property foreclosures, new
drivers, and household members.
Valuable information from law enforcement agencies, the court system,
licensing agencies, and health care providers was once obscure but is now
available and has a direct bearing on risks and claims—for those that know
how to obtain and analyze the data. Data from other insurance companies
and financial institutions is also available and useful in assessing risks,
spotting fraud, and settling claims. Telematics technologies are maturing,
providing information that creates a win-win scenario for insurers and
insureds. The insurer gets data on vehicle locations, mileage, and driving
behavior to improve risk assessment, and the consumer gets more control
over their premiums. Finally, a wide range of information is now geocoded,
enabling location based intelligence to be added to the equation. In
summary, the world of external data is changing rapidly. Insurers that take
advantage of this emerging supplemental data have the opportunity to gain
new insights to help drive top line growth and improve profitability.
Leveraging New Analytics Models and Services
Insurers able to build on their foundation of existing data and supplement
that with robust new information are two steps ahead of their competition.
While the data has value in itself, the ultimate payoff is in the intelligent
application of analytics tools and engines to the data. Insurers should
consider three primary types of models and services: business intelligence,
traditional analytics, and predictive analytics. Core business intelligence
software analyzes historical information, produces reports, and highlights
key results. Business intelligence capabilities are typically used for
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Insurers that take advantage
of this emerging supplemental
data have the opportunity to
gain new insights to help
drive top line growth and
improve profitability.
management planning purposes by shedding more light on the business
results. Traditional analytics tools give insurers more flexibility to spot
trends, identify patterns, and suggest corrective actions. Predictive models
analyze large volumes of information to identify future opportunities or
threats—for products, channels, segments, or even individual customers.
An integrated platform
for data and analytics
Integrating Data & Analytics Enterprise-Wide
provides both business
All insurers should create a platform for enterprise-wide data and analytics
to continue to expand and grow with their capabilities. Integrating data and
analytics across the enterprise is essential for supporting the entire policy
lifecycle (see Figure 2). Rather than retrieve external or internal data to
support an individual transaction, data and related insights from analytics
are stored and readily available for use later in the lifecycle.
and technology benefits.
The execution of a data and analytics strategy requires a technical platform
that eliminates silos and supports reuse across the enterprise. Two
dimensions of this platform must be considered:
Source: SMA 2011
Figure 2. Advanced Insurance Policy Lifecycle: Data is leveraged across the
enterprise.
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• Data Platform. A common architecture and toolset supporting the
foundational internal and external data along with the supplemental
emerging data. All data must be clean, accurate, timely, consistent, and
organized for easy accessibility.
• Analytics Services. A unified arsenal of engines and tools working
together to provide the analytics capabilities required.
An integrated platform for data and analytics provides both business and
technology benefits. The technology benefits include lower total cost
of ownership, improved reuse, optimized data acquisition costs, and
simplified maintenance due to standardization. The business benefits
include enhanced ability to segment the market, highly targeted marketing
strategies, better alignment of price to risk, improved customer service and
retention, and ultimately profitable growth.
Successfully leveraging data
and analytics is about
more than overcoming
technological challenges.
Its foundation is based on a
solid business strategy that
Winning in a Saturated Market
requires data capture and
SMA recommends four guidelines for an overall approach to data
and analytics:
integration throughout the
• Understand your current situation. Gain a clear understanding of the
policy lifecycle.
current data and analytics capabilities within your enterprise, and the
data and analytics available from outside sources.
• Define your strategy and plan. Develop your integrated business and
IT strategy and plan, and determine specific capabilities required to
support your plan. This is where strategy meets action—enabling you to
get started on an executable plan.
• Share data and analytics across the lifecycle. Reuse data and build
more value with each usage. Insurance enterprises are complex and
continually evolving, creating many technical and organizational
challenges to data sharing. An enterprise data strategy should be an
ongoing important element of the business and technology strategy.
• Continuously expand use of data and services. Recognize that
this isn’t a project that you will finish at a specific point in the future.
Proactively seek out and take advantage of new opportunities to
leverage data and analytics.
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Successfully leveraging data and analytics is about more than overcoming technological challenges. Its foundation is based
on a solid business strategy that requires data capture and integration throughout the policy lifecycle. SMA recommends that
insurers:
• Capture data early in the lifecycle. Gather data that may not be needed for the immediate transaction (be opportunistic).
• Use analytics modeling tools. Challenge assumptions and identify trends (such as changing shopping behaviors).
• Link processes together in new ways. Create more opportunities for growth and competitive advantage
(e.g., claims/marketing, underwriting/claims, and new business/marketing).
Gathering data early, using analytics tools, and linking processes allows insurers to take a sophisticated approach to growth.
By understanding consumer shopping behaviors, insurers are able to improve conversions, enhance risk evaluation, and offer
competitive pricing tied to the information about the consumer. Capturing and leveraging more data near the beginning of
the lifecycle enables insurers to identify fraud early on, and focus on retention efforts throughout the lifecycle. The improved
understanding of risks and enhanced customer service will result in lower claim frequencies and severities. Data integration and
automation will also simplify compliance reporting and reduce costs.
A competitive, saturated market like property and casualty personal lines in North America always results in winners and losers.
Winning in this market requires insurers to take bold actions to set themselves apart. Leveraging data and analytics across the
insurance lifecycle enables insurers to employ differentiating strategies to win—including advanced market segmentation,
sophisticated matching of price to risk, and superior customer service and retention strategies. Insurers that build a platform for
growth based on data and analytics will leap ahead and capture the market opportunity now.
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About Strategy Meets Action
Exclusively serving the insurance industry, Strategy Meets Action (SMA) blends unbiased research findings with expertise and
experience to deliver business and technology insights, research, and advice to insurers and IT solution providers. By leveraging
best practices from both the management consulting and research advisory disciplines, SMA’s services are actionable,
business-driven, and research-based—where strategy meets action—enabling companies to achieve business success.
The content of this white paper, sponsored and distributed by LexisNexis, was developed using SMA’s research-based
views and experience.
Additional information on SMA can be found at:
www.strategymeetsaction.com.
SMA Partner Mark Breading can be reached at:
[email protected] or 614 562 8310.
SMA Founder Deb Smallwood can be reached at:
[email protected] or 603 770 9090.
About LexisNexis® Risk Solutions
LexisNexis Risk Solutions (www.lexisnexis.com/risk) is a leader in providing essential information that helps customers across
all industries and government predict, assess and manage risk. Combining cutting-edge technology, unique data and advanced
scoring analytics, Risk Solutions provides products and services that address evolving client needs in the risk sector while upholding
the highest standards of security and privacy. LexisNexis Risk Solutions is part of Reed Elsevier, a leading publisher and information
provider that serves customers in more than 100 countries with more than 30,000 employees worldwide.
Our insurance solutions assist insurers with automating and improving the performance of critical workflow processes to reduce
expenses, improve service and position customers for growth.
For more information:
[email protected] or 877 719 8805.
This white paper is presented by LexisNexis on behalf of the author. The opinions may not represent the opinions of LexisNexis. This document is
for educational purposes only and does not guarantee the functionality or features of LexisNexis products identified.
LexisNexis, Lexis, Nexis and the Knowledge Burst logo are registered trademarks of Reed Elsevier Properties Inc., used under license. Other products and services
may be trademarks or registered trademarks of their respective companies. Copyright © 2011 LexisNexis. All rights reserved. NXR01686-0 0711
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