Applying Analytics for More Actionable Claims Information

By Michael Rivers

More and more insurers are recognizing the benefits of using business intelligence and analytics to improve claims decision making — and with good reason. These tools help people do their jobs more efficiently and more effectively, resulting in a positive impact on the bottom line. With recent staff reductions, an aging workforce, office centralization, and increasing claim severity, the claims department has an ever-increasing need for such solutions.

Business intelligence and analytics offer insights into claims data that adjusters and claims management might not otherwise discover because of time or experienced-based constraints or a lack of comprehensive analysis. These tools can help determine which claims are straightforward and can be closed quickly and which claims are more complex or contain questionable elements that require further investigation and information.

When claims professionals act on intuition alone, they are "following a notion." Their preconceived ideas about a situation may or may not be supported when scrutinized by business intelligence tools. In many situations, analytics will augment claims professionals' background and experience to provide more actionable information and better claims outcomes.

For example, some claims managers may believe that the number of strains in soft-tissue spine strain cases (whiplash) is not positively correlated to claim payment. Some believe the payment to be the same regardless of having injuries to multiple spine body parts. However, a review of the data reveals that this belief is false.

The dashboard example in Figure 1 below provides a simple focus on bodily injury (BI) claim closures, revealing that double and triple strains can be 40 percent and 80 percent higher than single-strain claim payments, respectively. This example offers accurate information, but it may not be directly actionable because a more serious injury should have a higher payment. By applying analytics, however, the claims manager may answer a related question that is actionable.

What if further analysis revealed that BI closures consisted of more double and triple strains during one year than the year before? The dashboard in Figure 2 includes a "settled date" trend showing an increase in 2007 compared with 2006. What conclusions would an insurer reach based only on preconceived ideas? If the claimant demographic has remained the same (for example, no marked increase in the age of claimants due to population shift), it would be impossible to guess the reason for the upswing. However, if a focused audit were applied to the claims, results might reveal that recently hired staff members require additional training. Here is a case where analysis of information creates a call for action: Management knows what the problem is and has a strategy to solve it and, ultimately, improve operations.

Figure 1
COA Dashboard: Bodily Injury Claim Closures

COA Dashboard: Bodily Injury Claim Closures

The examples in this article support the idea that if you can't measure it, you can't fix it. They illustrate the importance of focusing on analytics as well as on information collection.

Analytics tools also offer the ability to discover actionable insights in the form of key performance indicators (KPI). KPIs are the principal measures of business performance. Changes in cycle time or medical severity are possible KPIs for a claims department. If these indicators change over time, preconfigured flags can notify management immediately. Applying analytics to KPIs is a much more efficient and reliable way to determine when something important has changed when compared with depending on a busy manager to realize there is cause for concern. KPI flags can function as e-mail alerts, social media posts, or special graphics on system displays.

When claims managers rely on intuition, they depend on their own past experiences and knowledge. For example, few claims professionals would be surprised to find that claim payment trends in Cook County, Illinois — the Chicago metropolitan area — differ from the rest of the state. The trends follow standard geographic boundaries. However, business intelligence and analytics offer greater insight and can show that trends in Cook County, Illinois, are similar to those in Richmond, Virginia, and Philadelphia, Pennsylvania.

Figure 2
COA Dashboard: Settled Date Trend

COA Dashboard: Settled Date Trend

When insurers decide to consolidate or centralize offices, this actionable information can be used to identify a better staffing model that matches adjuster experience to the venues supported by the remaining offices. Variables that could be used to compare one office to another, in addition to the venue itself, may include the injury descriptions of claims (soft-tissue back strains combined with other demonstrable injuries such as a fracture or hernia), the underlying medical severity, and the accepted form of treatment for the injuries within the same venue.

There is no doubt that experience counts. Claims adjusters will always be needed for investigations and negotiations. When managers build on that personal experience by supporting the data with analytics, they can move beyond hunches and discover more actionable information. From individual claim payments to enterprisewide initiatives, the application of analytics helps insurers develop strategies, improve performance, and achieve their goals.

Michael Rivers is manager, claims analytics and consulting services, ISO Claims Services.