Abstract
M.Com. (Financial Management)
The rural poor with no physical collateral typically have virtually no access to small business financing. The microfinance movement replaces physical collateral with social collateral as a means for rural poor persons to gain access to financing for their microbusinesses. Microfinance entails lending to self-formed groups of close-knit community members who are jointly liable for loans advanced to individual group members. Advantages include borrower screening by fellow group members, mutual assistance in micro-enterprises, monitoring repayment and imposing social sanctions to delinquent group members. Despite the use of group lending, Microfinance Institutions (MFIs) are still faced with the risk of default by borrowers and the absence of physical collateral means there is no recourse to borrower assets for repayment. Default on loans, which can be caused by characteristics of the lending groups themselves, has the undesirable effect of eroding the capital base of MFIs and threatening their continued existence. The main research problem is that MFIs are faced with borrower default that threaten their operational sustainability. The main purpose of this study is to investigate the effect of group characteristics on the probability of borrower default. The characteristics of interest are: the age and gender of the borrower, group size, loan amount, instalment size, loan duration, loan cycle, location of group (rural or urban), business experience of the borrower, business savings, business assets, record of loan centre meeting attendance, family relations in a group and intra-group business risk correlation. The importance of this understanding will practically assist MFIs with insights regarding which factors to eliminate and which to enhance in the design of the groups to which they lend.
The probit regression model was used on secondary data from a loan programme at a large South African MFI. The key findings of the study indicate that probability of default decreases with larger groups, more female borrowers in a group and larger borrower savings. We also found that probability of default increases with larger loan...