During the past decade, companies across the insurance industry have invested tens, or even hundreds, of millions of dollars in claims transformation. These programs became an imperative for carriers struggling with processing effectiveness and data management issues, and facing the risks of regulatory non-compliance and loss of market share.

Legacy claims operating models and technology systems limited the ability of insurers to compete in the modern marketplace, with its quickly rising consumer demands and urgent need to reduce processing costs. Without claims transformation, efficiency levels and performance were simply not where they needed to be for insurers to effectively compete.

These first-phase transformation initiatives largely focused on replacing or upgrading core claims processing platforms to improve operations and productivity. However, a significant number of carriers that achieved baseline success with initial transformation programs have not yet fully harvested the value of the vast amounts of data they now capture. That's why forward-thinking organizations now look beyond the initial value propositions of increased speed, quality, and efficiency in claims processing to Claims Transformation 2.0 initiatives, which are focused on harnessing the power of advanced business intelligence (BI).

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

These insurers are focused on the technology, analytics, process, and organizational refinements that will keep them ahead of evolving consumer needs, and protect them against competitive threats. They are looking to enhance their new operational environments and translate their technological capabilities and increased data assets into tangible, bottom-line financial results and sustainable competitive advantage. They are actively preparing today to leverage tomorrow's advancements in claims technology.

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

High-impact role of BI and analytics in Claims Transformation 2.0, especially as they relate to customer experience and claims fraud
Technology evaluation and selection questions
Unique dynamics associated with data presentation to internal and external audiences
Strategic, tactical and cultural implications of the shift toward an outcome-based, data-driven decision-making approach within claims operations.

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

BI and better decisions

Much of the focus in first-phase transformation initiatives was on efficiency, cost containment and the mitigation of risks associated with internal and external regulatory compliance. By finding the right claims processing and management platform to enable increased efficiency and better information capture, insurers sought to improve outcomes and enhance productivity. That meant finding the vendors and tools with the functionality, integration options, scalability and price points that suited the company's needs.

Given the rapid pace of innovation and advancement in the claims technology market, the same approach must be taken to move forward with second-generation initiatives, with one critical difference: the emphasis must now shift from replacing legacy claims platforms to enhancing decision making and performance management. Put another way, second-generation success moves from improving the claims-handling process to creating business value through the effective and intelligent use of claims data. Typically, that involves extending core claims platforms with advanced analytics and BI toolsets that enable claims adjusters, managers and executives to make more objective, informed and outcome-driven decisions at every decision point in the claims lifecycle.

Advanced analytics enables enhanced leverage of rules-based engines to drive automated processing for a higher percentage of claims. By understanding value drivers, such as claims cycle times, closing ratios, escalation points, and segmentation, analytics can help determine best practices, identify improvement opportunities and influence how a claims professionals' time is most profitably spent. The higher levels of operational efficiency that such engines enable can free claims leaders to focus on the most strategic and value-adding elements of claims handling and management. For example, they can begin to drill down on facts and follow trends in claims files to identify “hot-button” issues and “red flags” associated with potentially fraudulent claims or vulnerable policies approaching renewal. Resources can then be directed to high-value activities.

Relative to enhancing the customer experience, advanced analytics can facilitate improved customer relations, as better data on claims processes and outcomes can help insurers manage claimant expectations on claim resolution and timeframes. Communications can also be refined and enhanced as insurers can identify optimal times and touch points to reach out to claimants and third parties – such as within 24 hours of the first notification of loss or at other key times during the investigation phase. The ability to support context-based communication via mobile applications is another area of rich opportunity for insurers to explore — and a hallmark of next-phase claims initiatives.

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

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

A closer look at how insurers address these questions reveals the various challenges and requirements necessary for Claims Transformation 2.0 success. After implementing new systems and integrating new data streams (some of which may be external), insurers should assess their information management and analytical technologies and toolsets, and look for opportunities to upgrade them. First, they must understand the full range of data now available to adjusters, analysts and claims executives, recognize the value of all elements in the data set, and then figure out who needs to see what, when and through which interface or toolset.

To properly utilize the data now available, the organization should review the actions taken throughout the life of a claim to determine and improve upon decision making. Active reviews and audits of the claim-handling process can reveal gaps and opportunities where better data and more robust analytics can improve outcomes. This is the essence of next-phase claims transformation.

Empowering users and optimizing data delivery

Claims Transformation 2.0 initiatives look beyond data from internal systems and internal user groups to leverage valuable external data sources and to connect external data users. While the initial focus of internal data optimization is rightfully set on establishing strong data infrastructure, access and security protocols, usage by agents/brokers and other third parties is perhaps the richer strategic territory to examine in next-phase claims transformation programs. Specifically, carriers must seek ways to facilitate useful data exchange so that they enhance their own analytical capabilities, and strengthen relationships with distribution forces and clients.

For instance, many agents and brokers sell, or provide as a value-added service, analytical reports regarding carriers' books of business. Comparisons with the agent's own book of business are often included. This is data to which carriers typically do not have access. Carriers can potentially support agents and brokers in this endeavor by providing direct access to internal systems; however, doing so requires different presentation layers, data modeling (e.g., to allow slicing and dicing of claims by broker within a carrier book), and support capabilities (e.g., a help desk equipped and trained to provide support to external users). Alternatively, carriers may need to integrate their data warehouses with 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 and presentation models must fit the organization, both in terms of technology and culture. Specifically, insurers will need to determine if and how mobile technologies will be supported. Questions about help desk support and liability issues must also be addressed.

There are ample security concerns as well. Security models must be concrete and relevant. Legal and regulatory issues related to medical data, consumer privacy and personally identifiable information must be vetted and formally addressed through clear policies and protocols.

User expectations must be documented and socialized throughout business and technology organizations. The needs of diverse user bases must be recognized. For instance, external users such as brokers may require different views of and access to account data, while internal users may vary in terms of skill set and needs. The broad range of analytics skills, knowledge and expectations among different audience groups will drive requirements.

Some analysts may need truly advanced capabilities for ad-hoc querying and self-service analysis. Other audiences may be satisfied with high-level dashboards and standard reports. The C-suite may be very interested in analytics in theory, but have limited practical exposure. Management and supervisory levels may have very focused needs and interests, as will individual contributors. Similarly, role-based authorizations and access clearance must be accounted for in the design phase of both system and data architectures.

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

Carriers must also figure out if and how social media and text mining—to name just two data-related trends—can be utilized in the next step of the claims transformation process. A number of powerful tools to help insurers in these areas have emerged and are becoming more prevalent. As they mature, carriers must give some long-term thought to the optimal data warehouse topology, and how they will get the best value going forward. As you can see, claims transformation programs will continue to evolve, and soon may resemble ongoing optimization initiatives built directly into steady-state operations.

Managing the shift to new decision-making models

When embedding BI and analytics into claims-handling processes, insurers must recognize that the move to an objective, data-driven decision-making model represents a major cultural shift. For some in the claims organizations, the transition will be a fundamental change from comfortable ways of working. Struggles are likely, even for those workers who recognize that an objective, data-driven approach is superior. Successful culture change requires that the claims organization examine the broad organizational impacts, and achieve full buy-in from all necessary parties and stakeholders.

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

When filtering through significantly larger amounts of data, the organization may fall victim to confirmation bias, a phenomenon in which analysts and executives focus on data points supporting their own, pre-existing hypotheses. Incorrect “anchoring”—which occurs when a decision maker references new data incorrectly off of a specific point of information or value—can also prevent an organization from fully digesting, properly interpreting or fully harvesting the value of new information assets.

The big idea is to ensure that organizations view BI and analytics as a strategic means for measuring, managing and, ultimately, improving business performance. This requires that they fully leverage the data that is produced by their new claims management platforms, and assure that geographically dispersed claims supervisors and adjuster teams adopt the new decision-making frameworks and criteria.

Further, improvements must be translated to KPIs that are tracked in bottom-line financial results, and data must be used to promote organizational performance and personal accountability. Specific objectives and goals should be established so that BI initiatives and teams have targets to work toward. Leadership across the enterprise must embrace and advocate for the new BI-driven processes and enhanced analytical approach to decision making. Such support will be useful in building near-term momentum for the new way of working.

Lastly, organizations must ensure they have the right analytical resources and teams in place. It may sound clichéd to say that any technology is only as effective as the person using it, but the experience of advanced analytics in insurance confirms the truth of the observation. Providing the right resources with an environment that supports the development of analytical skills and rewards creativity in analyzing and presenting data will do a great deal to foster an analytics culture (as well as to boost adoption rates for new tools and processes).

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

Transforming for long-term value creation

The rapid evolution of claims operations and technology in the last five to seven years suggests that transformation is not a process with clearly fixed start and end dates. Indeed, the carriers that largely fulfilled the business case of their first-phase initiatives have discovered the significant value associated with building on their solid foundations with advanced BI and analytics capabilities in second-phase initiatives.

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

In the meantime, for firms that have established strong, highly automated platforms for claims processing, the Claims Transformation 2.0 business case is about building on the gains from Claims Transformation 1.0. Yes, there are quantifiable gains to be captured through an improved customer experience for claimants (a proven driver of loyalty), reduced risk of fraud, and stronger, sustainable quality assurance programs. But now that the claims function has significantly more data, insurers must focus on finding the actionable insights within that data to unlock hidden value. In this sense, Claims Transformation 2.0 can redefine how claims units make decisions, and focus their energies and talents to further contribute to the business.

Special Reports /

Out with the Old: Smarter Systems Help Insurers Achieve Claims Transformation

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