For the liability claims organization everything revolves around the exposure model. Accurate exposure prediction is the key to effective claim handling on the individual claim level, and is vital to the efficiency and consistency of the organization as a whole. At the individual claim level, an exposure driven approach results in effective claim triage that assigns services based upon predicted exposure. At the organizational level the exposure driven approach allows the organization to develop the most efficient staffing models for the types and quality of claims being handled by the organization.
In this series of articles we will examine how a liability decision support system that is structured around an exposure driven approach philosophy can result in more effective claim handling and increase the efficiency and effectiveness of the organization as a whole. The series consists of four articles, each of which will cover in depth one element of the claims management process and how that element can be enhanced through the application of an exposure driven approach philosophy.
The first article in the series will cover what we refer to as Triage and Investigation, and how the exposure model for a claim should be the driving factor in the management of that claim throughout its lifecycle. We will also examine how an exposure driven approach can affect organizational dynamics and staffing models.
The second article in the series will focus on Workload Quantification and how an understanding of the exposure model allows for the most efficient assignment of claims, (i.e., the right adjuster for the right claim), and how that exposure model also determines the amount of work required to resolve the claim.
The third article will look at the liability decision support system and how it needs to be Adaptive to the exposure prediction model on a continuing basis throughout the claim lifecycle. We will examine the concept of the liability decision support system being a platform rather than a product, and how, depending upon the exposure model, it can bring to bear the proper tools at the proper time in the claim cycle so that the claim can be resolved in the most optimal manner possible.
Finally we will look at Measurement and Peer Comparisons through the prism of the exposure driven approach. We’ll examine the need for user “tunabilty” of both exposure thresholds and the toolsets available to the liability decision support system. And we will close the series with a recap and overview of how a liability decision support system with advanced exposure modeling capabilities will benefit the claim organization at both the adjuster and organizational level.
Triage and Investigation – Day One Prediction, Claim Assignment, Claim Management, Organizational Dynamics, and Staffing Models
An accurate exposure prediction for each and every claim, throughout the lifecycle of that claim, (from first notice of loss through final settlement), is the cornerstone of any successful claims organization. Having a reliable exposure model allows the claims organization to triage claims and assign adjusters and resources to maximize productivity and efficiency, and minimize the cost of the claim handling process.
In medicine triage is the process of determining the priority of treatment by sorting casualties based upon the severity of their injuries. In claims the concept of triage can be thought of as assigning adjusters and resources to manage a claim based upon the exposure prediction for that claim. Obviously the sooner that a claims organization can make an accurate exposure prediction for a claim, the more efficiently and cost-effectively that claim can be resolved. A liability decision support system that has both an effective exposure prediction model and the ability to allocate tools that are appropriate for the types and exposure levels of the claims assigned to the adjuster is an invaluable asset for any claims organization.
Exposure Driven Claim Assignment
One of the key elements in developing the most effective and efficient claims organization is assigning the right person, with the right skill set, to the appropriate level claim. The importance of initial claim assignment based upon potential exposure was noted in an article in Claims Magazine by Rebecca C. Amoroso:
A claims talent crisis is looming with a projected shortage of more than 85,000 adjusters by 2012. With the number of expert adjusters dwindling, initial assignment of claims to the right resource is more important than ever. By better understanding a claim’s true exposure, explosive cases are quickly directed to the most qualified adjusters while low-exposure claims are channeled to less experienced resources or auto-adjudication. (August 2008, p1)
While the need for proper initial claim assignment may seem obvious, the complexity of accomplishing that seemingly simple task becomes readily apparent when you consider an organization with hundreds, or even thousands of adjusters, each at a different competency level, handling hundreds or thousands of new claims daily.
By utilizing the exposure prediction model of a trusted liability decision support system as the basis for assigning claims to adjusters, the claims organization has a built in mechanism for enforcing consistency of assignment that most efficiently utilizes the talents and skills of its adjusters, no matter what their level of expertise.
By having the ability to assign the right adjuster as early as possible in the claim handling process, the claims organization can also minimize adjuster reassignments during the life of the claim. Reassignments are costly to insurers on multiple levels – they increase the time period needed to settle a claim (making it more likely a claim will enter litigation), they involve duplication of effort (increasing labor costs), and they generally are a major source of consumer complaints involving insurer claim practices. Author Rod Travis, an executive vice president for a management consulting firm specializing in the insurance industry, noted in the Consultants Corner blog of Insurance Networking News, the role that information technology (of which the liability decision support system is a key element) can play in assigning adjusters:
IT can improve financial results by partnering with claims departments to deliver stronger claims automation and better analytics from claims data. This can help identify cases with potentially higher losses, enabling early and appropriate intervention. One simple example is flagging low-severity soft tissue injuries. Such claims warrant a more senior adjuster be assigned. (April 12, 2011, p1)
Exposure Driven Claim Management
Claims are dynamic, with their classification and complexity frequently changing during the life of the claim. These changes must be continuously monitored by a liability decision support system that dynamically reacts to each change with an updated and current exposure prediction model. That model in turn should be the basis for assigning adjusters to a claim based upon their strengths and skills as well as providing a framework and tool set that will best allow the assigned adjuster to most efficiently handle the claim.
Changing elements within a claim represent a dynamic environment in which a liability decision support system can play two important roles. First, the system should be able to assess the effects of any changes on the exposure prediction value for the claim. A 2005 Business Insurance article in which author Rupal Parekh interviewed claims technology expert Donald Light of Celent Communications, touched upon the importance of this liability decision support system function:
To help determine what is fair and accurate for both claimants and the insurance company, some online systems now provide suggested settlement amounts, using a rules engine, Mr. Light noted. For example, in the case of a bodily injury such as a broken leg, systems are available that can provide the adjuster with the average settlement amounts based upon geographic-specific medical costs. (May 1, 2005, p12)
Parekh quoted Mr. Light as saying of these systems, “For newer adjusters, especially, that takes away the likelihood of making a human error.” (May 1, 2005, p12)
The other important role of the liability decision support system is to assist the adjuster in the investigation of the claim by suggesting and making available investigative tools and resources that are tied to the initial or changing circumstances of the claim. The tools best suited for the investigation of a claim are almost wholly dependent on the exposure potential of the claim. If exposure potentials are initially high, or if they should change significantly during the life of the claim, a sophisticated liability decision support system should be able to suggest to the adjuster the most appropriate investigative resource.
For example a sudden and significant change in medical specials midway through the investigation of a claim, could trigger the liability decision support system to suggest to the adjuster that a specialized impact analysis be performed. Tools that predict the probability and severity of injuries based upon an impact study of the underlying accident, could be helpful in determining if the change in medical specials is warranted.
Staffing Models and Organizational Dynamics
A liability decision support system that is focused on exposure can also be the lead element in determining the most efficient staffing model for the claims organization. The data that the liability decision support system uses in creating exposure prediction models for individual claims can also be used on a macro level across the claims organization as a whole, to create an optimal staffing model by providing a basis for the quantification of different exposure events.
Developing a staffing model that matches adjuster skill sets and event quantification and that also provides a means of modeling actual claim workloads (and the exposure level across those workloads), is a formidable but absolutely essential task. On his insurance-related blog, The Claims SPOT, Marc Lanzkowsky addresses the issue of developing a staffing model. “Having a staffing model will allow you to objectively look at your operation and help determine if it’s a good time to hire more staff” (May 3, 2010, p1). He lists 3 suggestions for creating a staffing model. First says Lanzkowsky, determine:
- What kind of organization are you?….Understanding the strategic position of your claims organization is critical to understanding what kind of staffing model is relevant.
- Decide on a metric to develop your model: The metric you choose will help to determine the model, but will be wholly based upon the types of claims organization you are….Maybe your claims settle quickly, as in some property matters, so the number of new claims a handler receives in a month is a more critical metric…
- You now have the metric – test the staff and come up with the model: Once you settle on a metric, check your top performers against the new metric you have selected. How many files are they handling and still managing files within best practices? At what point does their ability to manage those files well breakdown? Take an average of the top performer’s metrics and you will have a staffing model to give you a benchmark. (May 3, 2010, p1)
Using exposure models as the metric which Mr. Lanzkowsky refers to in his second point in the above quote can allow the claims organization to match the skill sets of its staff to the actual types and exposure levels of its claims inventory. Matching adjuster staff skill levels against the claims inventory exposure levels is an effective method of developing a staffing model that is made possible through the exposure driven approach philosophy.
The above methodology also gives the claims organization the operational flexibility to monitor changes in claim types, volumes, and exposure levels and adjust its staffing requirements in a timely manner to reflect those changes.
A liability decision support system that provides advanced exposure modeling capabilities will benefit the claims organization on multiple levels. At the adjuster level it will increase the efficiency and consistency of the claims handling process. At the organizational level it will assist in developing staffing models that accurately reflect the true operational needs of the organization.
Amoroso, Rebecca C. (August, 2008). Science Project – Tech Decisions. Claims Magazine Retrieved 6/2/2011 from: http://www.propertycasualty360.com/2008/08/01/science-project
Lanzkowsky, Marc. (May 3, 2010) “Does Hiring More Staff Improve Claims? How To Know When The Time Is Right.” The Claims SPOT – SPOT on Ops Retreived 6/2/2011 from: http://theclaimsspot.com/2010/05/03/does-hiring-more-staff-improve-claims-how-to-know-when-the-time-is-right/
Parekh, Rupal. (May 5, 2005, p12) “All Systems Go; Automating claims processing systems can speed up processing and boost the bottom line.” (Cover Focus: Information Technology). Business Insurance. Retrieved 6/1/2011 from: Expanded Academic ASAP (Infotrac): Subscription or Library membership required.
Travers, Rod. (April 12, 2011) “5 Steps for Insurers to Maximize Profitability. Insurance Networking News Claims Blog. Retrieved 6/6/2011 from: http://www.insurancenetworking.com/blogs/insurance_technology_IT_projects_profitability_growth-27652-1.html
(CC) June 2011 Vatti-Manhattan Group
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