The Comparative Analysis of Predictive Models for Credit Limit Utilization Rate with SAS/STAT®

Credit card usage modelling is a relatively innovative task of client predictive analytics compared to risk modelling such as credit scoring. The credit limit utilization rate is a problem with limited outcome values and highly dependent on customer behavior. Proportion prediction techniques are widely used for Loss Given Default estimation in credit risk modelling (Belotti and Crook, 2009; Arsova et al, 2011; Van Berkel and Siddiqi, 2012; Yao et al, 2014). This paper investigates some regression models for utilization rate with outcome limits applied and provides a comparative analysis of the predictive accuracy of the methods. Regression models are performed in SAS/STAT® using PROC REG, PROC LOGISTIC, PROC NLMIXED, PROC GLIMMIX, and SAS® macros for model evaluation. The conclusion recommends credit limit utilization rate prediction techniques obtained from the empirical analysis.