Text mining for insurance claim cost prediction

  • Authors:
  • Inna Kolyshkina;Marcel van Rooyen

  • Affiliations:
  • PricewaterhouseCoopers, Sydney, Australia;PricewaterhouseCoopers, Sydney, Australia

  • Venue:
  • Data Mining
  • Year:
  • 2006

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Abstract

The paper presents the findings of an industry-based study in the utility of text mining. The purpose of the study was to evaluate the impact of textual information in claims cost prediction. The industrial research setting was a large Australian insurance company. The data mining methodologies used in this research included text mining, and the application of the results from the text mining in subsequent predictive data mining models. The researchers used software of the leading commercial vendors. The research found commercially interesting utility in textual information for claim cost prediction, and also identified new risk management factors.