• DocumentCode
    1280000
  • Title

    Probabilistic estimation-based data mining for discovering insurance risks

  • Author

    Apte, Chidanand ; Grossman, Edna ; Pednault, Edwin P D ; Rosen, Barry K. ; Tipu, Fateh A. ; White, Brian

  • Author_Institution
    IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA
  • Volume
    14
  • Issue
    6
  • fYear
    1999
  • Firstpage
    49
  • Lastpage
    58
  • Abstract
    IBM´s underwriting profitability analysis application mines property and casualty insurance policy and claims data to construct predictive models for insurance risks. UPA uses the ProbE data-mining kernel to discover risk-characterization rules by analyzing large, noisy data sets
  • Keywords
    data mining; insurance data processing; IBM´s underwriting profitability analysis application; ProbE data-mining kernel; insurance risks; noisy data sets; predictive models; probabilistic estimation-based data mining; risk-characterization rules; Companies; Data mining; Electrical capacitance tomography; Insurance; Kernel; Predictive models; Probes; Profitability; Risk analysis; Sensitivity analysis;
  • fLanguage
    English
  • Journal_Title
    Intelligent Systems and their Applications, IEEE
  • Publisher
    ieee
  • ISSN
    1094-7167
  • Type

    jour

  • DOI
    10.1109/5254.809568
  • Filename
    809568
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1280000