An Analysis of Determinants of Missing an Installment Payment in Motorcycle Hire Purchase Business: A Case Study of a Company in Bangkok

Abstract

This research aimed to study factors causing missing an installment payment in motorcycle hire purchase business and solutions for reducing non-performing loans in those companies. Secondary data obtained from 1,500 people who bought motorcycles with hire purchase agreement were analyzed using the Logit Model. Moreover, primary data collected from in-depth interviews with 40 staff members who are responsible for collecting overdue balances were analyzed using the descriptive method.  

The results of the secondary data analysis revealed that factors leading to missing an installment payment included gender, income, career, having a guarantor, marital status, length of work experience, credit limit, interest rate, down payment amount, poor credit history recorded by the National Credit Bureau, and number of installments. Such results were consistent with those of the primary data analysis. The marginal effects causing a decrease in missing an installment payment included having a high income, having a guarantor, having a long period of work experience, a high down payment amount, and long-term installments. Meanwhile, marginal effects causing an increase in missing an installment payment included being male, owning a business, working for private companies, working as government officials, working freelance, being married, receiving a high credit limit, paying a high interest rate, and poor credit history recorded by the National Credit Bureau. Important qualifications of preferred debtors with a low risk of missing an installment payment included being female, working as farmers, having a guarantor, being single, and having a good credit history recorded by the National Credit Bureau. Important qualifications of non-preferred debtors with a high risk of missing an installment payment included being male, working freelance, having no guarantors, being married, and having a poor credit history recorded by the National Credit Bureau.

This research recommended that the credit approval process should be conducted based on the analysis of credit scoring using the equation suggested by this research. Concerned companies were recommended to approve credits for those with a credit score of A, to take a special care when approving credits for those with a credit score of D, and not to approve credits for those with a credit score of E.