A Data Mining framework to model Consumer Indebtedness with Psychological Factors

February 20, 2015 ยท Declared Dead ยท ๐Ÿ› 2014 IEEE International Conference on Data Mining Workshop

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Authors Alexandros Ladas, Eamonn Ferguson, Uwe Aickelin, Jon Garibaldi arXiv ID 1502.05911 Category cs.LG: Machine Learning Cross-listed cs.CE Citations 10 Venue 2014 IEEE International Conference on Data Mining Workshop Last Checked 3 months ago
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.
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