An Integrated Data Mining Approach to Premium Pricing for the Automobile Insurance Industry

A. C. Yeo and K. A. Smith
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A. C. Yeo: Monash University School of Business Systems, PO Box 63B, Victoria 3800, Australia
K. A. Smith: School of Business Systems, Faculty of Information Technology, PO Box 63B, Monash University, Victoria 3800, Australia

Chapter 5 in Intelligent and Other Computational Techniques in Insurance:Theory and Applications, 2003, pp 199-227 from World Scientific Publishing Co. Pte. Ltd.

Abstract: AbstractThe following sections are included:IntroductionA Data Mining ApproachRisk Classification and Prediction of Claim CostRisk ClassificationK-Means Clustering ModelFuzzy CMeans Clustering ModelHeuristic ModelPrediction of Claim CostK-Means Clustering ModelFuzzy C-Means Clustering ModelHeuristic ModelResultsPrediction of Retention Rates and Price SensitivityPrediction of Retention RateNeural Network ModelDetermining Decision ThresholdsAnalyzing Prediction AccuracyGenerating More Homogeneous ModelsCombining Small ClustersResultsPrice Sensitivity AnalysisResultsDetermining an Optimal Portfolio of Policy HoldersResultsConclusionsReferences

Keywords: Insurance; Actuarial Science; Neural Networks; Fuzzy Systems; Computational Intelligence; Computational Techniques; Life and Health Insurance; Property and Casualty Insurance (search for similar items in EconPapers)
Date: 2003
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