ESTIMATING THE DETERMINANTS OF VEHICLE LOAN DEFAULT IN MALAYSIA: AN EXPLORATORY STUDY

Abstract

As revealed by Malaysia’s bankruptcy statistics, around a quarter of bankruptcy in Malaysia is due to default of vehicle loan. This has led to the tightening up of vehicle loan underwriting and increased vehicle loan rejection rates. The need for a better credit risk scoring model is also raised by the banks. This warrants a study to estimate the determinants of vehicle loan default in Malaysia. This paper estimates the determinants of vehicle loan default probability which could be used to build a loan default prediction or forecasting model for credit risk scoring purposes. Using a simple random sample of 138 car loan borrowers that was provided by an established bank in Malaysia, the descriptive statistical procedures and econometrics modelling were performed to unveil these vehicle loan default determinants. Results of descriptive statistics revealed that more than half of the borrowers were default. Results of logit models further revealed that loan related characteristics are the most important determinants of probability of default. Specifically, the significant determinants of loan default were: areas of residence, vehicle purchase price, length of service, existing relationship with bank, interest rate, and available guarantor. Borrowers who are in high risk of default are characteristically those who reside in rural areas, secure higher vehicle purchase price, have longer length of employment service, are borrowers new to the bank, acquire loans charged with high interest rates, and are without a guarantor.
Keywords: Loan default; Vehicle loan; Logit model; Forecasting model.