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Using Argumentation to Develop a Set of Rules for Claims Classification

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Intelligent Decision Technologies (IDT 2017)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 39))

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Abstract

The first step in insurance claims processing is the classification of accident types, for example work-related or domestic accidents, using a set of business rules. In some cases the rules are ambiguous, so a claim is assigned more than one possible classification. If the process is to be automated, the rule set should allow for as few ambiguities as possible, because every ambiguous match requires human intervention. In this paper, we present a technique based on argumentation theory for minimising the number of ambiguous matches in the development of a set of decision rules. We evaluate our approach with a case study and some theoretical results.

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Notes

  1. 1.

    The concept model of accident types is in reality quite complex and can even involve requests for additional (master and application) data from other IT systems, the modelling of which is a challenge in itself.

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Author information

Authors and Affiliations

  1. SAP UK Ltd, The Concourse, Queen’s Road, Belfast, BT3 9DT, UK

    Jann Müller

  2. AOK Systems GmbH, Breitlacher Str. 90, 60489, Frankfurt, Germany

    Tobias Trapp

Authors
  1. Jann Müller
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  2. Tobias Trapp
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Corresponding author

Correspondence to Jann Müller .

Editor information

Editors and Affiliations

  1. FCT, Universidade Nova de Lisboa, Caparica, Portugal

    Rui Neves-Silva

  2. Faculty of Education, Science, Technology and Mathematics, University of Canberra, Canberra, Australia

    Lakhmi C. Jain

  3. KES International, Shoreham-by-sea, United Kingdom

    Robert J. Howlett

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Müller, J., Trapp, T. (2015). Using Argumentation to Develop a Set of Rules for Claims Classification. In: Neves-Silva, R., Jain, L., Howlett, R. (eds) Intelligent Decision Technologies. IDT 2017. Smart Innovation, Systems and Technologies, vol 39. Springer, Cham. https://doi.org/10.1007/978-3-319-19857-6_39

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  • DOI: https://doi.org/10.1007/978-3-319-19857-6_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19856-9

  • Online ISBN: 978-3-319-19857-6

  • eBook Packages: EngineeringEngineering (R0)

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