I. Introduction
Despite being movable assets, capital expenditure on passenger cars have assumed higher order of importance next to housing. Luxury cars indicate the wealth of a household and are thus an important tangible asset. Banks and various credit assessment agencies evaluate the wealth of individuals based on the passenger cars owned by them. If the risk of default in the automotive finance is 10–15%, the risk involved in lending in case of luxury segment is around 5–7%. Interestingly, since the value of the luxury passenger cars is significant, despite lower volume of default, the incidence of default is higher. Hence this study focuses on identifying the determinants of default using multiple methods like ANOVA, regression and decision trees on a luxury passenger car consumer data set in order to understand the variables and the methodology used in earlier studies, the study commenced with the review of empirical evidence.