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Classification in automobile insurance using a DEA and discriminant analysis hybrid

✍ Scribed by Donna Retzlaff-Roberts; Robert Puelz

Book ID
104649834
Publisher
Springer
Year
1996
Tongue
English
Weight
773 KB
Volume
7
Category
Article
ISSN
0895-562X

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✦ Synopsis

In this article, we adopt an efficiency approach to the hvo-group linear programming method of discriminant analysis (DA), using principles taken from data envelopment analysis (DEA), to predict group membership in an insurance underwriting scheme. Using an empirical insurance data base we illustrate the effectiveness of our model as a decision-making tool to distinguish among automobile insurance applicants by contrasting our hybrid model with both statistical and LP methods of discriminant analysis. We find for this insurance application that our hybrid model significantly outperforms the more traditional methods in separation and misclassification outcomes.

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✍ Toshiyuki Sueyoshi; Mika Goto πŸ“‚ Article πŸ“… 2011 πŸ› Elsevier Science 🌐 English βš– 228 KB

This study discusses a combined use of DEA (Data Environment Analysis) with SCSC (Strong Complementary Slackness Condition) and DEA-DA (Discriminant Analysis). Many studies use DEA to evaluate the performance of various organizations in private and public sectors. A conventional use of DEA is not pe