A Data Mining Framework to Model Consumer Indebtedness with Psychological Factors

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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Year of publication:	2016
Authors:	Ladas, Alexandros
Other Persons:	Ferguson, Eamonn (contributor) ; Aickelin, Uwe (contributor) ; Garibaldi, Jonathan (contributor)
Publisher:	[2016]: [S.l.] : SSRN
Subject:	Data Mining \| Data mining \| Konsumentenverhalten \| Consumer behaviour

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