• DocumentCode
    174879
  • Title

    eXsight: An Analytical Framework for Quantifying Financial Loss in the Aftermath of Catastrophic Events

  • Author

    Coelho, Matthew ; Rau-Chaplin, Andrew

  • Author_Institution
    Fac. of Comput. Sci., Dalhousie Univ. Halifax, Halifax, NS, Canada
  • fYear
    2014
  • fDate
    1-5 Sept. 2014
  • Firstpage
    165
  • Lastpage
    170
  • Abstract
    In this paper we explore the design of an analytical framework for quantifying financial loss in the aftermath of catastrophic events. The idea is to aggregate the thousands of exposure databases received by a single reinsurer into a giant loosely structured exposure portfolio and then use Big Data analysis technology, originally developed in the context of web-scale analytics, to rapidly perform natural but ad-hoc loss analysis immediately after an event. As in many situational analysis problems, the challenge here is to work with both categorical and geospatial data, deal with partial data often at varying levels of aggregation, integrate data from many sources, and provide an analysis framework in which analyses can be rapidly performed in the hours, days, and weeks immediately after an event.
  • Keywords
    Big Data; data analysis; financial data processing; investment; Big Data analysis technology; Web-scale analytics; adhoc loss analysis; analytical framework; catastrophic events; categorical data; data aggregation; eXsight; exposure databases; financial loss quantification; geospatial data; loosely structured exposure portfolio; partial data; reinsurer; situational analysis problems; Companies; Data models; Databases; Earthquakes; Geospatial analysis; Hazards; Servers; MongoDB; Risk analytics; catastrophe; exposure data; framework; post-event; reinsurance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Database and Expert Systems Applications (DEXA), 2014 25th International Workshop on
  • Conference_Location
    Munich
  • ISSN
    1529-4188
  • Print_ISBN
    978-1-4799-5721-7
  • Type

    conf

  • DOI
    10.1109/DEXA.2014.45
  • Filename
    6974844