There can be tremendous value gained to the underwriting process when underwriters "know" what is going on in the book of claims. Yet claim operations and technologies have traditionally existed in their own separate silos, away from the processes technologies that support the underwriting process.
Despite the traditional separation, claim data that developed as a "normal part of good claim handling" can be combined with common underwriting data to provide powerful rating information and insight. When that insight is paired with the appropriate rules engine and workflow technologies, it can drive actions to improve underwriting results.
Premium Rating Errors Can Be Very Expensive
For many auto insurers, annual miles driven, commute use, and commute mileage are key rating factors. According to a 2010 report by Quality Planning Corporation, these common rating elements are also the leaders in rating errors that cost insurers an estimated $3.1 billion in lost premiums each year. The report also points to discrepancies in vehicle usage, vehicle characteristics, rated territory, rated operators, and vehicle/driver assignments that add another $7.7 billion to the estimated $15.9 billion in annual rating error premium loss.
Certainly a series of regular and consistent audits, reviews, and inspections can help reduce these costs as well as ensure that adequate rates are charged for the risk represented. Each of these processes, however, comes with a cost to the insurer and potential inconvenience to the insured. The inconvenience could create resistance that may drive a portion of an insurer's book to the arms of competitors with less stringent requirements.
A claim investigation can provide pieces of data that underwriters may need in order to validate the type and quality of the risk in comparison to what information is contained in the underwriting file. Smart carriers know this, and have processes in place by which the claim handler can alert the underwriter to items that may be of rated risk concern.
Most carriers still follow a traditional paper-based method of communicating this type of information. This process is slow, cumbersome, and takes the focus of the adjuster away from handling the claim to a non-system supported manual exception process. The consistency, timeliness, quality, and value of this exchange can be further diminished by adjusters if they are:
- Not being fully cognizant of what type of information is important to the underwriting community (which is a potential burden to the underwriting community as well...);
- Not recognizing the importance of reporting potential underwriting inconsistencies to an insurer's ability to price risk appropriately and ensure competitive pricing across their policy book or;
- Working under the assumption that underwriting will identify the issue and resolve them through their standard risk review processes.
Overlaying these issues are the priorities of the claim adjuster, who place the provision of top quality claim handling service over filling out paper forms for the underwriting organization.
Systems Can Talk to Each Other
A simple auto collision or comprehensive loss necessitates the collection of the mileage of the insured vehicle. Including the "annual miles driven" data element in the coverage download sent to the claim system at the initiation of the claim allows the claim system to quickly compare the rated mileage to the actual mileage. The system can then provide an automated alert back to the underwriter as appropriate.
For instance, if the insured vehicle is a 2008 model rated for "less than 10,000 miles per year" and a loss in December 2010 shows vehicle mileage at 40,000 miles, something is amiss and the appropriate premium may not be being collected for the underwritten risk. If the opposite is true, the insurer has an opportunity to recalculate the lower annual mileage rate and the potential to offer the insured a reduction in premium.
Let's explore some other examples based upon the leading reasons for auto rating errors. In these cases, automated flags might be created through a straight-forward comparison of claim and underwriting data, both within and across lines of business.
Rating Error Claims/Underwriting Flag
Commute
Selected repair location or medical provider more than set radius from garage location or reported work address
Vehicle Usage
Number and ages of passengers in personal use rated vehicle, weekend use of commercial use rated vehicle
Vehicle Characteristics
Repair estimate includes large number of non-OEM or non-industry standard parts suppliers such as performance part vendors. "Temporary substitute vehicle" listed on loss involving a non-owned high performance vehicle
Unrated Operators
Permissive use indicated as "relation to insured" on vehicle loss notice
Vehicle/Driver Assignment
Claim incident location in relation to garage location, comparison of demographics of assigned vehicle driver with items stolen from vehicle (in the case of an auto break-in with both glass loss and companion homeowner's claim).
What About Other Lines of Business? CLICK NEXT
Workers' Compensation
Insurance Services Office (ISO) reports that insurance industry losses due to workers' compensation fraud are as high as $5 billion each year. They also estimate that, for every $1 lost through claimant fraud, at least $4 to $5 is lost through premium fraud.
Though it is certain that not all rating errors are due to deliberate malfeasance on the part of the insured, similar types of comparisons between data elements contained in the claim file to those in the underwriting file can highlight areas for the possibility of further rate adequacy investigation.
If the commercial insured has an automobile accident, what number is the damaged vehicle listed on the policy? Is this number above the number of fleet vehicles indicated on the workers' compensation policy? Does the accident or repair location fit within the radius of operation for a commercial automobile policy from the fleet garaging location?
Comparing the North American Industry Classification System (NAICS) code contained in the underwriting file to the injury type reported in the claim file can also be a key indicator of potential rating discrepancies. For instance, if the insured's NAICS code is listed as 453110 (florists; fresh flower shops) and the workers' compensation claim is for a burn (ICD-9 range 940-949) this is likely important information for the underwriter to be aware of.
If the insured is pursuing a business interruption claim under their commercial property policy, does the payroll amount listed in the property claim file match the payroll amount contained in the workers' compensation underwriting file?
General Liability
If a workers' compensation claim codes the injured worker's occupation as a bartender or cocktail server and the insured location is listed as a liquor store in the general liability underwriting file, an inappropriate rate may be being charged. Likewise, a covered contents claim under the commercial property policy at this same insured premises indicating contents damage to a pool table, juke box, or pinball machines could be a potential flag for the general liability underwriter.
Claim information that indicates insured contracts containing embedded subrogation waivers or liability limitation limits may also be of interest to the underwriter. The insurer may wish to add these discrete data elements as "yes/no" choices in their claim handling database.
Homeowners'
When repair estimates are prepared for structure and contents claims, do their details as captured in the claim and/or estimating systems match the "what should be" information in the underwriting file? Do structural repair materials make sense for the construction type? Does the contents claim match to the reported use? For instance, high volumes of computer equipment or a large amount children's furniture and toys reported in the claim file may point to an un-rated home business exposure.
Similarly, contents claims for damaged pet supplies or equipment can point to the presence of an unrated animal on the premises.Liability claims for dog bites are an ever increasing concern. An August, 2010 report by the Insurance Information Institute indicates that dog bites were the basis for more than one-third of all homeowners insurance liability claims paid in 2009 and accounted for $412 million in claim payments. This same report stated that these payments have grown 30 percent in the past six years.
The Importance of Information
Information developed during the claim handling process can add substantial benefits to the underwriting rating and pricing decision process. The straight-forward collection and comparison of discrete data elements commonly found in both claim and underwriting systems, combined with system enabled business rules and execution logic can provide significant value to ensuring that appropriate knowledge of the risk is made available to the underwriter. This allows the provider with the ability to make adequate rating and pricing decisions that are consistently executed across the policy book.
There are a few simple to moderately complex scenarios by which this process can bring useful information to the underwriter's desk without disrupting the prompt, efficient, cost effective, and service sensitive claim handling process that every insurer is dedicated to providing.
Mike Mahoney is the Senior Director of Product Marketing, Auto Casualty Solutions at Mitchell International, Inc. He may be reached at [email protected].
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