Credit Card Customer Spending Analysis - Follow Up

Conducted a regression analysis for a major credit card company to evaluate how demographic factors (such as gender, education, marital status, age, and bill amounts) impact customer payment amounts and default likelihood. Built and analyzed two models: one predicting average payment amounts and another estimating default probability, leveraging qualitative data through dummy variable coding. Interpreted model results and checked for endogeneity, multicollinearity, heteroskedasticity, and non-linear patterns, recommending targeted insights for risk assessment and customer segmentation strategies. Supported findings with professional Tableau visualizations to facilitate strategic decision-making.