Distinguishing between good and bad subprime auto loans borrowers: the role of demographic, region and loan characteristics

Yaseen Ghulam, Sophie Hill

    Research output: Contribution to journalArticlepeer-review

    336 Downloads (Pure)

    Abstract

    Research on subprime mortgages has recently been gaining momentum, but subprime auto loans have largely been ignored. By using a unique data set of a very large UK vehicle finance company, this study analyses secured loans extended to the subprime borrowers with impaired or limited credit history. It looks specifically at characteristics in relation to payment history, in order to determine what characteristics make a good or bad borrower. We conclude that married and divorced borrowers as well as borrowers living in low unemployment and relatively prosperous regions such as the South East and London are less likely to default compared to not married, furnished tenants or borrowers living in the North West of the UK who have a high probability of default. Similar to the prime loans, income of borrowers and defaults propensities are negatively associated. Loan and security characteristics with the most impact on default status are price and age of the automobile, effective interest rate measured by APR, loan-to-value (LTV) and term of the loan agreement. The results of this study will help in understanding subprime auto loans and borrowers as well as helping lenders to distinguish between good and bad subprime borrowers.
    Original languageEnglish
    Pages (from-to)49-62
    Number of pages14
    JournalReview of Economics and Finance
    Volume10
    Issue number4
    Early online date7 Dec 2017
    Publication statusEarly online - 7 Dec 2017

    Keywords

    • automobile loans
    • defaults
    • subprime
    • credit risk
    • UK

    Fingerprint

    Dive into the research topics of 'Distinguishing between good and bad subprime auto loans borrowers: the role of demographic, region and loan characteristics'. Together they form a unique fingerprint.

    Cite this