Alexandros Ladas,Eamonn Ferguson,Uwe Aickelin,Jon Garibaldi
Abstract URL: http://arxiv.org/abs/1502.05911v1
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.