• DocumentCode
    243510
  • Title

    A Data Mining Framework to Model Consumer Indebtedness with Psychological Factors

  • Author

    Garibaldi, J. ; Ferguson, E. ; Aickelin, U.

  • Author_Institution
    Sch. of Comput. Sci., Univ. of Nottingham, Nottingham, UK
  • fYear
    2014
  • fDate
    14-14 Dec. 2014
  • Firstpage
    150
  • Lastpage
    157
  • Abstract
    Modelling Consumer Indebtedness has proven to be a problem of complex nature. In this work we utilise Data Mining techniques and methods to explore the multifaceted aspect of Consumer Indebtedness by examining the contribution of Psychological Factors, like Impulsivity to the analysis of Consumer Debt. Our results confirm the beneficial impact of Psychological Factors in modelling Consumer Indebtedness and suggest a new approach in analysing Consumer Debt, that would take into consideration more Psychological characteristics of consumers and adopt techniques and practices from Data Mining.
  • Keywords
    consumer behaviour; data mining; psychology; consumer debt; consumer indebtedness; data mining framework; data mining technique; psychological characteristics; psychological factors; Analytical models; Biological system modeling; Data mining; Data models; Economics; Predictive models; Psychology; Consumer Debt Analysis; Data Mining; Impulsivity; Psychological Factors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining Workshop (ICDMW), 2014 IEEE International Conference on
  • Conference_Location
    Shenzhen
  • Print_ISBN
    978-1-4799-4275-6
  • Type

    conf

  • DOI
    10.1109/ICDMW.2014.148
  • Filename
    7022592