Whether we want to blame technology, precarious organizational channels, or overall public perceptions regarding insurance fraud, the first step is to admit that silos between underwriting and claims exist and must be eliminated. Period. Both claims and underwriting need to share data, and “good” data at that so fraudsters do not sliver their way into lower-than-adequate premium calculations or inappropriate or undeserved claims payouts.

As is the case with many things, successfully identifying suspicious activity and possible rating discrepancies begins with adopting a cohesive strategic vision and then translating that vision to a series of linked, goal-oriented tactical actions.   Within this priority, each insurance carrier must cultivate an overall fraud-mitigating philosophy that takes into account department-specific resources.

“An insurer must figure out what its overall fraud philosophy is and what its ultimate goal will be,” advised Mike Mahoney, senior director of product marketing at Mitchell Auto Casualty Solutions. “Where do you want to go? Or, on a more granular level, is your aim to deny the potentially fraudulent claim or simply have it go away? Do you plan to prosecute or to seek reimbursement? Without an answer to this, it is virtually impossible to establish the right people, processes, and technology to effectively combat claim— or premium—fraud.” Mahoney points out that many insurers make the mistake of fixating on one aspect of the problem or organization. One carrier may focus on optimizing the capabilities of its SIU, whereas another may focus primarily on technological kinks. He also illustrates that insurer complacency and accepting fraud as “a necessary evil of doing business” is an exercise in futility and extremely damaging to the industry's fraud-fighting efforts on the whole.

“To put it all in perspective, let's suppose there is a 5-percent burglary rate in my area,” he explained. “If I consider this just 'part of the neighborhood,' I focus my efforts inward—such as putting bars on my windows—with no guarantee of success versus outward—such as being part of a neighborhood watch—where the entire neighborhood in engaged in eliminating the issue and punishing the perpetrators.”

For insurers, preventing money from going out the door involves apportionment of SIU, claims, and underwriting resources in such a way as to execute a smooth loss-mitigation program that keeps all invested parties on high alert, yet not feeling burdened with extra steps outside of the daily demands of the job.

There are definitive data links that can be identified between claims data and potential premium fraud. To this end, management may need to emphasize to harried adjusters with brimming caseloads that placing useful information on the underwriter's desk—even if figuratively speaking—is essential. The secret is to do it in a way that is integrated with day-to-day claims data collection and handling practices that will not divert attention from the time-sensitive claims-handling process.

“Back in the day, the adjuster almost didn't want to flag suspicious claims,” Mahoney said. “Already working an extensive case load, the fraud-savvy adjuster would have to fill out a form, photocopy the claim file, and then send it all to the SIU to examine the case. If the SIU decides not pursue the case at that point or devotes a significant amount of time investigating [a dead end], then the claim will go back to the adjuster, who has lost [precious] days of potential claim progress and most likely will be accepting back a more difficult case to settle.”

There are gentle avenues to enable adjusters to be more cognizant of claim fraud without obstructing the handling process. Insurers should evaluate the work flow and tools necessary to achieve heightened awareness, while adjusters must have a convenient way to share information that will be of interest to underwriters as they assess risk. In lieu of a paper-based system by which claims would have to step away from the file and manually complete forms, a carrier should employ a system allowing transmission of automated alerts to underwriting when necessary. This could entail a series of prompts and pull-down menus, with cross-claims business analytics. In regard to business intelligence, a company can program a pattern to be recognized. When actual technology implementation begins, the insurer can draw from the collective knowledge of its top claims fraud experts and incorporate that knowledge within the claims handling systems. For instance, let's say you recover a stolen vehicle that is now a charred mess. Was the policyholder having financial problems or unemployed?

Quantifying “Quality” Data
Top claims professionals can generally define the logic they use to flag worrisome details. However, we would be remiss without mentioning predictive analytics as part of the carrier's solution. In mining the right data, the carrier can discover new patterns. Once these patterns have been identified, they can be programmed, so the capability to recognize and mitigate claims fraud is constantly evolving.

“In regard to predictive analytics' potential impact on claims fraud, studies from as recently as 2007 pointed to a typical reduction of 3 to 5 percent in claims costs, with some carriers attaining savings as much as 5 to 10 percent,” Mahoney said.

When measuring the quality of your data, there are two crucial parameters: the right information and accurate information. Often insurers will have multiple and duplicate data systems. Consider, for instance, a claim involving the theft of a vehicle. The claimant alleges the car was snatched from a Manhattan address. However, the adjuster may not know the underwriting information—namely, that the policy covers the car as being stored at a garage location in upstate New York. The policyholder also claims to only drive 10,000 miles each year. So which record is now accurate? Who can update this information?

Let's look at other hypothetical examples of when it is advantageous to compare reported claim facts to data in the underwriting file:

• A workers' compensation claim is filed for a hot tar burn. The insured business is reported as a florist.
• A business interruption (BI) claim reporting wage loss for more employees than stated in workers' compensation underwriting file and/or underwriting file indicates “independent contractors” used for duties reported that the injured party was engaged at the time of incident. 
• A general liability for damage to property in insured care, custody and control when the underwriting file indicates the insured business as “do-it-yourself” equipment rental.
• Injury to “for hire passenger” when the underwriting file indicates no such exposure. 
• A homeowners' liability claim for a slip and fall where the injured party was at the premises to pick up a child from day-care. This begs the question of what does the property underwriting file say about “business on premises.”

So how far can combined quality data, claims-handling savvy, and advance analytics can take an insurer? “The absolute upper limit might be a measure against banking efforts in reducing credit card fraud,” Mahoney said. “About 85 percent of U.S. credit card transactions are screened for fraud, with reports of reductions as high as 50 percent in card fraud. While this is a great benchmark, it is important to recognize the differences between credit card transactions and the complexities of a claim file.  Compared to a claim, a credit card fraud model may be relatively simple, as card-holder purchase patterns are easy to establish, based upon multiple transactions, and with few data points per transaction to sample—basically where, when, what, and how much. With claims fraud, an insurer may have one claim and then never see that perpetrator again.” Aside from consumer fraud, another primary cause for rating errors is the inability of insurers to keep track of some key life events and driving habits of their customers. The sidebar on the opposite page summarizes the findings of a recent report on premium leakage as it pertains to auto and touches on how seemingly small changes can have a large impact on risk and the corollary underwriting decisions.

Because our lives are in a constant state of flux, carriers must serve as an insured's “life event partner” in a way. This means initiating contact to stay attuned to whether a policyholder's son is going off to college, for example. Will he need a laptop, which may necessitate a rider designed for students?

Establishing an effective leakage detection program will help to solidify a partnership between the policyholder and the insurer while breaking down barriers so that underwriters and claims can work as impassioned allies in the fight against fraud. Direct contact—in addition to curbing losses related to premium and claims—will pave a smoother road for all in the winding journey ahead.