White Paper. High Value Data and Analytics: Building a Platform for Growth

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1 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.

2 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 2

3 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. 3

4 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. One way to gain a competitive advantage is to gain a better understanding of, and capitalize on, consumer shopping behavior. 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 4

5 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 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. The successful execution of key competitive strategies is, in many cases, hampered by the availability of the right data and analytics capabilities. 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. 5

6 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. Limited Use of External Data and Analytics 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). 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. Source: SMA 2011 Figure 1. Traditional Insurance Policy Lifecycle: Data Supports Individual Transactions. 6

7 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. Data and Analytics as Differentiators 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. Building on Your Foundational Data Successfully leveraging data and analytics is based on a solid business strategy that requires data capture and integration throughout the policy lifecycle. 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). 7

8 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. 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 8

9 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. Integrating Data & Analytics Enterprise-Wide 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. An integrated platform for data and analytics provides both business 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. 9

10 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. Winning in a Saturated Market SMA recommends four guidelines for an overall approach to data and analytics: Understand your current situation. Gain a clear understanding of the current data and analytics capabilities within your enterprise, and the data and analytics available from outside sources. 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. 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. 10

11 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. 11

12 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: SMA Partner Mark Breading can be reached at: mbreading@strategymeetsaction.com or SMA Founder Deb Smallwood can be reached at: dsmallwood@strategymeetsaction.com or About LexisNexis Risk Solutions LexisNexis Risk Solutions ( 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: insurance.sales@lexisnexis.com or 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. NXR