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Illustrating the Explicative Capabilities of Bayesian Learning Neural Networks for Auto Claim Fraud Detection

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

Author

Listed:
  • S. Viaene

    (Leuven Institute for Research in Information Systems (LIRIS), Naamsestraat 69, B-3000 Leuven, Belgium)

  • R. A. Derrig

    (Automobile Insurers Bureau of Massachusetts, Insurance Fraud Bureau of Massachusetts, 7th Floor, 101 Arch Street, Boston, MA 02110, USA)

  • G. Dedene

    (Applied Economic Sciences, Katholieke Universiteit Leuven, Dept. TEW Naamsestraat 69, B-3000 Leuven, Belgium)

Abstract

The following sections are included:IntroductionNeural Networks for ClassificationInput Relevance DeterminationEvidence FrameworkPIP Claims DataEmpirical EvaluationConclusionReferences

Suggested Citation

  • S. Viaene & R. A. Derrig & G. Dedene, 2003. "Illustrating the Explicative Capabilities of Bayesian Learning Neural Networks for Auto Claim Fraud Detection," World Scientific Book Chapters, in: A F Shapiro & L C Jain (ed.), Intelligent And Other Computational Techniques In Insurance Theory and Applications, chapter 10, pages 365-399, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789812794246_0010
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