During the past decade, companies across the insurance industryhave invested tens, or even hundreds, of millions of dollars inclaims transformation. These programs became an imperative forcarriers struggling with processing effectiveness and datamanagement issues, and facing the risks of regulatorynon-compliance and loss of market share.

Legacy claims operating models and technology systems limitedthe ability of insurers to compete in the modern marketplace, withits quickly rising consumer demands and urgent need to reduceprocessing costs. Without claims transformation, efficiency levelsand performance were simply not where they needed to be forinsurers to effectively compete.

These first-phase transformation initiatives largely focused onreplacing or upgrading core claims processing platforms to improveoperations and productivity. However, a significant number ofcarriers that achieved baseline success with initial transformationprograms have not yet fully harvested the value of the vast amountsof data they now capture. That's why forward-thinking organizationsnow look beyond the initial value propositions of increased speed,quality, and efficiency in claims processing to ClaimsTransformation 2.0 initiatives, which are focused on harnessing thepower of advanced business intelligence (BI).

Recent research from Gartner confirms that carriers see thevalue in BI. In 2012, 89 percent of property and casualty insurerswere already investing in BI, or planned to invest within the year.According to a survey of insurance CIOs, BI investment is thenumber one priority today. This survey further stated that 22percent of property and casualty insurers plan to invest directlyin claims analytics.

These insurers are focused on the technology, analytics,process, and organizational refinements that will keep them aheadof evolving consumer needs, and protect them against competitivethreats. They are looking to enhance their new operationalenvironments and translate their technological capabilities andincreased data assets into tangible, bottom-line financial resultsand sustainable competitive advantage. They are actively preparingtoday to leverage tomorrow's advancements in claims technology.

This article explores the issues and opportunities related toClaims Transformation 2.0 programs, and outlines the key buildingblocks to successfully turn data into knowledge, action andmeasurable results. Specifically, it will focus on the:

• High-impact role of BI and analytics in Claims Transformation2.0, especially as they relate to customer experience and claimsfraud
• Technology evaluation and selection questions
• Unique dynamics associated with data presentation to internaland external audiences
• Strategic, tactical and cultural implications of the shifttoward an outcome-based, data-driven decision-making approachwithin claims operations.

Additionally, it will help point the way forward and define theright first steps companies should take when startingsecond-generation initiatives.

BI and better decisions

Much of the focus in first-phase transformation initiatives wason efficiency, cost containment and the mitigation of risksassociated with internal and external regulatory compliance. Byfinding the right claims processing and management platform toenable increased efficiency and better information capture,insurers sought to improve outcomes and enhance productivity. Thatmeant finding the vendors and tools with the functionality,integration options, scalability and price points that suited thecompany's needs.

Given the rapid pace of innovation and advancement in the claimstechnology market, the same approach must be taken to move forwardwith second-generation initiatives, with one critical difference:the emphasis must now shift from replacing legacy claims platformsto enhancing decision making and performance management. Putanother way, second-generation success moves from improving theclaims-handling process to creating business value through theeffective and intelligent use of claims data. Typically, thatinvolves extending core claims platforms with advanced analyticsand BI toolsets that enable claims adjusters, managers andexecutives to make more objective, informed and outcome-drivendecisions at every decision point in the claims lifecycle.

Advanced analytics enables enhanced leverage of rules-basedengines to drive automated processing for a higher percentage ofclaims. By understanding value drivers, such as claims cycle times,closing ratios, escalation points, and segmentation, analytics canhelp determine best practices, identify improvement opportunitiesand influence how a claims professionals' time is most profitablyspent. The higher levels of operational efficiency that suchengines enable can free claims leaders to focus on the moststrategic and value-adding elements of claims handling andmanagement. For example, they can begin to drill down on facts andfollow trends in claims files to identify “hot-button” issues and“red flags” associated with potentially fraudulent claims orvulnerable policies approaching renewal. Resources can then bedirected to high-value activities.

Relative to enhancing the customer experience, advancedanalytics can facilitate improved customer relations, as betterdata on claims processes and outcomes can help insurers manageclaimant expectations on claim resolution and timeframes.Communications can also be refined and enhanced as insurers canidentify optimal times and touch points to reach out to claimantsand third parties – such as within 24 hours of the firstnotification of loss or at other key times during the investigationphase. The ability to support context-based communication viamobile applications is another area of rich opportunity forinsurers to explore — and a hallmark of next-phase claimsinitiatives.

Similarly, the right BI and analytics tools can help claimsexecutives address a range of critical questions to help redefineand optimize the way a company approaches claims management. Suchquestions may include:

• Are we using the right metrics to determine if cycle times arewithin the target parameters defined by claim type?
• Which data can we use to track exposure to help determine whenclaims will exceed reserve estimates?
• Do we have the right mix of adjuster skill sets and experienceto handle volatile claims, based on demographics and severity?
• Are systems and processes integrated with expert systems toimprove fraud detection and analysis?
• Are time of accident, frequency of incidents/claimant, creditscore/employment history, and other indicators of fraud included inescalation protocols?

A closer look at how insurers address these questions revealsthe various challenges and requirements necessary for ClaimsTransformation 2.0 success. After implementing new systems andintegrating new data streams (some of which may be external),insurers should assess their information management and analyticaltechnologies and toolsets, and look for opportunities to upgradethem. First, they must understand the full range of data nowavailable to adjusters, analysts and claims executives, recognizethe value of all elements in the data set, and then figure out whoneeds to see what, when and through which interface or toolset.

To properly utilize the data now available, the organizationshould review the actions taken throughout the life of a claim todetermine and improve upon decision making. Active reviews andaudits of the claim-handling process can reveal gaps andopportunities where better data and more robust analytics canimprove outcomes. This is the essence of next-phase claimstransformation.

Empowering users and optimizing datadelivery

Claims Transformation 2.0 initiatives look beyond data frominternal systems and internal user groups to leverage valuableexternal data sources and to connect external data users. While theinitial focus of internal data optimization is rightfully set onestablishing strong data infrastructure, access and securityprotocols, usage by agents/brokers and other third parties isperhaps the richer strategic territory to examine in next-phaseclaims transformation programs. Specifically, carriers must seekways to facilitate useful data exchange so that they enhance theirown analytical capabilities, and strengthen relationships withdistribution forces and clients.

For instance, many agents and brokers sell, or provide as avalue-added service, analytical reports regarding carriers' booksof business. Comparisons with the agent's own book of business areoften included. This is data to which carriers typically do nothave access. Carriers can potentially support agents and brokers inthis endeavor by providing direct access to internal systems;however, doing so requires different presentation layers, datamodeling (e.g., to allow slicing and dicing of claims by brokerwithin a carrier book), and support capabilities (e.g., a help deskequipped and trained to provide support to external users).Alternatively, carriers may need to integrate their data warehouseswith those used by brokers.

It is clear there are a range of challenges to be negotiated,and many details to be worked out. Delivery channels andpresentation models must fit the organization, both in terms oftechnology and culture. Specifically, insurers will need todetermine if and how mobile technologies will be supported.Questions about help desk support and liability issues must also beaddressed.

There are ample security concerns as well. Security models mustbe concrete and relevant. Legal and regulatory issues related tomedical data, consumer privacy and personally identifiableinformation must be vetted and formally addressed through clearpolicies and protocols.

User expectations must be documented and socialized throughoutbusiness and technology organizations. The needs of diverse userbases must be recognized. For instance, external users such asbrokers may require different views of and access to account data,while internal users may vary in terms of skill set and needs. Thebroad range of analytics skills, knowledge and expectations amongdifferent audience groups will drive requirements.

Some analysts may need truly advanced capabilities for ad-hocquerying and self-service analysis. Other audiences may besatisfied with high-level dashboards and standard reports. TheC-suite may be very interested in analytics in theory, but havelimited practical exposure. Management and supervisory levels mayhave very focused needs and interests, as will individualcontributors. Similarly, role-based authorizations and accessclearance must be accounted for in the design phase of both systemand data architectures.

Lastly, integration with third-party data, data warehousesystems and other data aggregators is another critical variable inthe equation. A third-party study conducted in the second quarterof 2012 found that 60 percent of all insurers plan investment in“big data” within the next two years, if not earlier. As big databecomes an operational reality for all types of carriers, the firmsthat harvest the most value from unprecedentedly large volumes ofboth structured and unstructured data will be those with theability to seamlessly integrate, find. and use the most valuabledata.

Carriers must also figure out if and how social media and textmining—to name just two data-related trends—can be utilized in thenext step of the claims transformation process. A number ofpowerful tools to help insurers in these areas have emerged and arebecoming more prevalent. As they mature, carriers must give somelong-term thought to the optimal data warehouse topology, and howthey will get the best value going forward. As you can see, claimstransformation programs will continue to evolve, and soon mayresemble ongoing optimization initiatives built directly intosteady-state operations.

Managing the shift to newdecision-making models

When embedding BI and analytics into claims-handling processes,insurers must recognize that the move to an objective, data-drivendecision-making model represents a major cultural shift. For somein the claims organizations, the transition will be a fundamentalchange from comfortable ways of working. Struggles are likely, evenfor those workers who recognize that an objective, data-drivenapproach is superior. Successful culture change requires that theclaims organization examine the broad organizational impacts, andachieve full buy-in from all necessary parties andstakeholders.

Broad cultural factors and specific human behavioral issues mustbe taken into account. When reviewing how analytics are used indecision-making processes, insurers must identify cognitive biasesthat exist in current processes. These biases, which may originatein marketing, underwriting, and other areas outside claims, canprevent full and proper usage of new data sources.

When filtering through significantly larger amounts of data, theorganization may fall victim to confirmation bias, a phenomenon inwhich analysts and executives focus on data points supporting theirown, pre-existing hypotheses. Incorrect “anchoring”—which occurswhen a decision maker references new data incorrectly off of aspecific point of information or value—can also prevent anorganization from fully digesting, properly interpreting or fullyharvesting the value of new information assets.

The big idea is to ensure that organizations view BI andanalytics as a strategic means for measuring, managing and,ultimately, improving business performance. This requires that theyfully leverage the data that is produced by their new claimsmanagement platforms, and assure that geographically dispersedclaims supervisors and adjuster teams adopt the new decision-makingframeworks and criteria.

Further, improvements must be translated to KPIs that aretracked in bottom-line financial results, and data must be used topromote organizational performance and personal accountability.Specific objectives and goals should be established so that BIinitiatives and teams have targets to work toward. Leadershipacross the enterprise must embrace and advocate for the newBI-driven processes and enhanced analytical approach to decisionmaking. Such support will be useful in building near-term momentumfor the new way of working.

Lastly, organizations must ensure they have the right analyticalresources and teams in place. It may sound clichéd to say that anytechnology is only as effective as the person using it, but theexperience of advanced analytics in insurance confirms the truth ofthe observation. Providing the right resources with an environmentthat supports the development of analytical skills and rewardscreativity in analyzing and presenting data will do a great deal tofoster an analytics culture (as well as to boost adoption rates fornew tools and processes).

If these cultural challenges are left unaddressed, currentclaims handling decision paths may remain in place, even after newtechnology has been installed and new process designs implemented.It is crucial that an organization be aware of these potentialpitfalls and take proper action to control them. In other words,full BI and claims transformation ROI requires some “rewiring” ofthe organizational brain.

Transforming for long-term valuecreation

The rapid evolution of claims operations and technology in thelast five to seven years suggests that transformation is not aprocess with clearly fixed start and end dates. Indeed, thecarriers that largely fulfilled the business case of theirfirst-phase initiatives have discovered the significant valueassociated with building on their solid foundations with advancedBI and analytics capabilities in second-phase initiatives.

There is reason to believe claims transformation programs willmorph into a state of permanent evolution or ongoing optimization.The urgency is equally high, too. Just as initial claimstransformation initiatives become “table stakes” requirements,ongoing claims transformation investments are likely to become acompetitive necessity as the claims function continues to grow inimportance as a strategic differentiator in the marketplace.

In the meantime, for firms that have established strong, highlyautomated platforms for claims processing, the ClaimsTransformation 2.0 business case is about building on the gainsfrom Claims Transformation 1.0. Yes, there are quantifiable gainsto be captured through an improved customer experience forclaimants (a proven driver of loyalty), reduced risk of fraud, andstronger, sustainable quality assurance programs. But now that theclaims function has significantly more data, insurers must focus onfinding the actionable insights within that data to unlock hiddenvalue. In this sense, Claims Transformation 2.0 can redefine howclaims units make decisions, and focus their energies and talentsto further contribute to the business.