While front-end functions like sales and underwriting are key facets of a successful insurance organization, the manner in which a carrier handles claims can make or break the company. Though the claim process may not directly add to an insurer's book of business, it often serves as the only touch point between a company and its policyholders.
Increasing consistency in the claim-handling process not only improves policyholder satisfaction but also delivers measurable results to enhance a carrier's bottom line. Advanced analytic technology and data-collection techniques can help an insurer settle similar claims in similar ways, leading to more adequate claim reserves, improved loss cost management, and more equitable settlements.
For successful insurers, the benefits can be substantial. According to the Insurance Information Institute's Insurance Fact Book 2010, nearly 30 percent—or $47.4 billion—of earned auto insurance premium was spent on bodily injury claims in 2008.
This is a significant sum, especially considering today's challenging economic environment. By increasing claim-handling efficiency, effectiveness, and consistency, insurers can better manage and mitigate the impact of such losses on bottom-line results.
What Are the Barriers to Achieving Claim Consistency? Click Next
Several barriers are inherent in the claim-handling lifecycle, and they impede efficiency and consistency in the process. These barriers include nonlinear claim-handling processes, frequent workflow interruptions, the complexity of certain cases, and multiple decision points.
The nonlinear nature of the claim-adjustment lifecycle poses a significant challenge to the claim-settlement process. An adjuster's ability to settle a claim in a timely manner largely depends on the available documentation and cooperation of the claimant. Furthermore, adjusters are often unable to complete a claim from beginning to end without some form of interruption, and they typically work on dozens of open claims at any given time.
Frequent interruptions coupled with a large workload can slow the progress of a settlement and even lead to erroneous decision making. Suppose an adjuster investigates an automobile accident and finds a third party is liable for the loss of property suffered by the policyholder. Just as the adjuster prepares to refer the claim to subrogation, a case manager calls regarding another urgent claim. Forced to switch gears quickly and abruptly to another open case, the adjuster may forget his intention to refer the first case to subrogation. That can delay the overall settlement process and carry substantial implications for the carrier's bottom line.
Bodily injury claims pose unique complexities for adjusters because of factors such as medical complications, multiple injuries, preexisting conditions, multiple reports from different health-care providers, claimant age, and so forth, compounding the challenge of achieving consistency. In fact, reaching reasonable and fair claim settlements often depends on the expertise and execution of individual adjusters. They are charged with collecting all relevant facts regarding the loss, thus ensuring a complete and thorough investigation, coverage verification, loss evaluation, and settlement negotiation.
Furthermore, throughout the claim-settlement process, the adjuster must make educated decisions regarding the claim, including whether there is potential for subrogation or if the claim appears to be suspicious and warrants further investigation for potential fraud. The adjuster must also determine the need for third-party intervention, such as a nurse or case manager, independent medical examiner, independent appraiser, or professional engineer.
Similarly, determining an appropriate return-to-work schedule for workers' compensation claims can vary widely from claim to claim, depending on the unique circumstances of the claimant's current and future medical condition as well as occupation and related physical demands. Further complicating matters is the number of parties that an adjuster must actively communicate with throughout the settlement process, including employees, employers, and all medical professionals involved.
An adjuster must take all such factors into account and decide whether the claimant can eventually return to his pre-injury occupation or if a return to an alternative occupation might be the preferred course of action. Obviously, a broken wrist would not affect an administrative assistant in the same way it would affect a construction worker. However, if an adjuster had additional information on hand, including a definition of the physical demands for each occupation, modified duties for the construction worker could possibly be implemented, thus minimizing lost time, claim expense, and reserve adjustments.
There are many challenges in the claim-handling lifecycle, and barriers to efficiency and consistency exist at many points in the process. However, at every significant decision point in the life of the claim, leveraging intelligent data collection, analyses, and analytic tools can improve claim-handling efficiency and consistency. Doing so requires carriers to collect high-quality data continually, conduct comprehensive and relevant analysis, and develop actionable decision rules for claim settlements.
The Power of Analytics and Data Management Revealed!
An insurer's ability to gather high-quality data regarding its claims is essential to understanding, analyzing, and assessing claim experiences effectively. High-quality data means data that is complete and reliable, yet easily accessible.
For instance, while "nature of injury" is a field that may be captured in a claim database, if it is not being entered on the majority of claims (or not entered in consistent format), it will be less useful for analysis. The data also must be easily accessible to those who will be performing the analyses. Carriers should devise data-collection strategies that take into account the analytic functions as well as the operational aspects of the claim process.
The more quality information an insurer has about its claim settlements, patterns, and trends, the better it can compare its performance against industry best practices. Moreover, quality data can be used to deploy advanced analytics programs designed to help adjusters manage complex claims. Such programs can examine and analyze thousands of data elements on various claims, both internal and external, and provide clear settlement guidelines to assist adjusters in some of the most difficult claim-related, decision-making processes, including determining liability in automobile accidents and developing effective back-to-work plans for workers' compensation cases.
Insurers with the most effective claim processes will apply analytic technologies continually across the lifecycle of a claim—from first report to settlement and recovery—creating multiple opportunities for assessments, reevaluations, recommendations, and ultimately better decisions as new information becomes available.
A company's claim experts and technology analysts can leverage algorithmic rules and build scenarios that analyze claim information in conjunction with various other resources. For instance in an injury claim, analytic programs can help examine medical references from multiple disciplines such as neurology, orthopedics, and chiropractics, among others. Insurers can use those analytic programs—integrated with claim administration and medical bill review systems—to build settlement guidelines based on the trauma, degree of permanent disability, loss of quality of life, and the company's own historical settlement trends.
Applying analytics throughout the claim lifecycle can also help adjusters quickly identify claims that can be referred to subrogation or fraud units for further examination. Text-mining analytics is one way to improve subrogation processes. Carriers often expect a certain percentage of claims to be referred to the subrogation unit. The subrogation adjusters are then required to investigate those claims, but they typically find that a number of claims should never have been referred to begin with—not to mention claims that should have been sent on for subrogation but were overlooked. Text mining can scan claim notes looking for indicators supporting subrogation, thus making sure the right claims are referred while minimizing false positives.
What About Other Analytic Tools? See next page!
Other analytic tools, such as link analysis and data visualization software, can further assist adjusters in determining whether a claim is suspicious. Like text mining, these tools can sift through large volumes of information and quickly flag hidden connections, such as a claimant linked to several addresses or Social Security numbers. Link analysis can also detect non-obvious connections, such as collusion between medical providers and attorneys. Referral patterns can reveal if a provider may be sending too many referrals to a facility in which they may have a financial interest. Without the aid of such tools, investigators might spend days or weeks combing through numerous documents to uncover such connections, if they could find them at all.
Insurers also can leverage these powerful data-visualization systems to analyze information from multiple internal and publicly available external sources to identify instances of fraud both outside and inside the company. Such analytics can help discover dishonest employees by flagging suspicious payments to an employee's relatives, or an adjuster that processes several out-of-network payments to non-preferred vendors not otherwise used by other adjusters in the area.
Predictive modeling and claim-scoring technologies can help adjusters identify the potential for subrogation and fraud. They can also be a useful tool that insurers can leverage to assist in the automatic assignment of claims to adjusters. Within the claim-handling workflow, automated scoring can identify less complicated claims for handling by junior adjusters and more complex cases for more experienced and skilled senior adjusters.
The impending retirement of many claim adjusters from the Baby Boomer generation is a growing concern among insurers and claim organizations, as managers and recruiters seek to tap a shrinking talent pool of workers while maintaining high-quality and efficient claim-handling processes. Employing advanced claim analytics and scoring can help bridge the talent gap by offering a framework for decision-making that all adjusters can use. These tools can help train less experienced claim handlers and provide senior-level expertise when dealing with more complex injury and liability claims.
Analytics and other information-driven, claim-management tools are an invaluable resource for providing the actionable information necessary to reach consistent and equitable claim settlements. These tools can help insurers produce significant bottom-line results and improved loss ratios—all of which are key components of a successful insurance enterprise.
