Implementing a Data Mining Solution for an Automobile Insurance Company: Reconciling Theoretical Benefits with Practical Considerations

Implementing a Data Mining Solution for an Automobile Insurance Company: Reconciling Theoretical Benefits with Practical Considerations

Ai Cheo Yeo (Monash University, Australia) and Kate A. Smith (Monash University, Australia)
Copyright: © 2006 |Pages: 13
DOI: 10.4018/978-1-59904-399-9.ch011
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Abstract

The insurance company in this case study operates in a highly competitive environment. In recent years it has explored data mining as a means of extracting valuable information from its huge databases in order to improve decision making and capitalise on the investment in business data. This case study describes an investigation into the benefits of data mining for an anonymous Australian automobile insurance company.1 Although the investigation was able to demonstrate quantitative benefits of adopting a data mining approach, there are many practical issues that need to be resolved before the data mining approach can be implemented.

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