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An Introduction to Neural Networks in Insurance

In: Intelligent And Other Computational Techniques In Insurance Theory and Applications

Author

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  • Louise A. Francis

    (Francis Analytics and Actuarial Data Mining, Inc., 706 Lombard St., Philadelphia, PA 19147, USA)

Abstract

The following sections are included:IntroductionBackground on Neural NetworksStructure of a Feedforward Neural NetworkExample 1: Simple Example of Fitting a Nonlinear Function to Claim SeveritySeverity Trend ModelsA One Node Neural NetworkFitting the CurveFitting the Neural NetworkThe Fitted CurveThe Logistic Function RevisitedExample 2: Using Neural Networks to Fit a Complex Nonlinear FunctionThe Chain Ladder MethodModeling Loss Development Using a Two-Variable Neural NetworkInteractionsCorrelated Variables and Dimension ReductionFactor Analysis and Principal Components AnalysisFactor AnalysisPrincipal Components AnalysisExample 3: Dimension ReductionConclusionAcknowledgmentsReferences

Suggested Citation

  • Louise A. Francis, 2003. "An Introduction to Neural Networks in Insurance," World Scientific Book Chapters, in: A F Shapiro & L C Jain (ed.), Intelligent And Other Computational Techniques In Insurance Theory and Applications, chapter 2, pages 51-102, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789812794246_0002
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    Cited by:

    1. Shapiro, Arnold F., 2004. "Fuzzy logic in insurance," Insurance: Mathematics and Economics, Elsevier, vol. 35(2), pages 399-424, October.

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