Because IPACC insures drivers who have higher incidences of accidents and claims, its profitability is highly dependent on its ability to identify fraudulent claims. It also needs to both maximize and accelerate the collection of subrogation payments, which are sought when a claim is the responsibility — or partial responsibility — of a driver who is not an IPACC policy holder.
In early 2007, IPACC began looking for ways to automate the workflows and data gathering related to fraudulent and subrogated claims. The identification of potentially fraudulent claims was the responsibility of claims adjusters who had varying degrees of training and used inconsistent practices. As a result, data related to potentially fraudulent claims was typically not gathered rapidly or completely enough. Speed of investigation and the early gathering of key data are both important for claims investigators. The prompt initiation of fraud investigation tends to reduce factors that inflate the values of fraudulent claims, such as the number of injured parties and the extent of their injuries.
In mid-2007, IPACC began looking for a solution that would enable the company to more rapidly identify and investigate suspicious claims. IPACC also wanted to be able to identify unsuspicious claims so that they could be handled rapidly in order to improve customer satisfaction. IPACC evaluated solutions from ChoicePoint, IBM, and SPSS. The SPSS solution was chosen for a number of reasons, including:
After purchasing SPSS in July 2007, IPACC assembled a team of three people from IPACC who spent five months deploying the solution. The deployment required:
SPSS was deployed in February 2008 and is used to identify suspicious claims before they are handled by investigators. Suspicious claims are forwarded to IPACC's 35 investigators who are now able to begin their investigations within days of a claim and have access to better data. Having used the tool to accelerate investigations and increase case closure rates, IPACC will soon utilize the textmining functionality to interpret and analyze the handwritten notes of claims adjusters so that they are more easily used in fraud investigations.
Adopting SPSS PredictiveClaims enabled IPACC to reduce claims payments and accelerate the collection of subrogation payments. Key benefits from the solution include:
Key cost areas for the deployment included software, consulting, personnel, and hardware. The solution was deployed over a 5-month period by three employees of IPACC and three consultants from SPSS who assisted with construction of rules for data analysis and script building. At the end of the deployment, four employees received a week of training from SPSS. Software costs consisted of SPSS licenses and maintenance. Three new servers were deployed to support the project.
Although IPACC started using SPSS for claims, it chose SPSS over other applications because it could be expanded to additional business uses within and outside the claims department. For example, IPACC recently purchased an additional license for its actuarial area for customer retention and pricing analysis. As IPACC continues its deployment of SPSS, it plans to analyze how it can gain more value by both identifying new potential applications and how it can collect data from additional sources for more effective predictive modeling.
IPACC is also using its knowledge from the initial deployment to fine-tune the application and make it a more integrated part of call center operations. For example, when a call center representative records a claim, the solution will continually reevaluate the claim as new details are entered into the system. Based on the interpretation of the claim, the application will give the call center representative a different response for the claimant based on whether the claim is likely to involve fraud, unlikely to involve fraud, or if more fraud-related data is needed. Because the proper questions will be asked — and the proper data gathered — during the first contact, SPSS will help IPACC to further streamline its claims management process.
Nucleus calculated the costs of software, consulting, personnel, hardware, and training over a 3-year period to quantify IPACC’s total investment in SPSS.
Direct benefits calculated included both avoided costs related to fraudulent claims and higher collection rates on subrogated claims. Indirect benefits consisted of accelerated collection of these claims. The value of avoided costs related to fraudulent claims was based on the increase in the number of successful investigations resulting from the deployment. The benefit from higher collection rates on subrogated claims was quantified based on the increased number of referrals to the subrogation claims department resulting from SPSS.
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