A Data Mining framework to model Consumer Indebtedness with Psychological Factors
This work addresses consumer debt analysis for financial or psychological researchers, but it appears incremental as it builds on existing data mining methods with added psychological factors.
The paper tackled modeling consumer indebtedness by incorporating psychological factors like impulsivity using data mining techniques, confirming their beneficial impact and suggesting a new approach that integrates more psychological characteristics.
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.