Abstract
Small Medium Enterprises (SMEs) in developing countries are subject to higher degree of information opacity causing substantive constrains on lenders in their pursuit of predicting credit risk associated with SME lending. Driven by this context, the lending for SMEs is often characterized as relationship lending and credit risk predictions therefore necessarily resort to qualitative information which is often deemed to be the cost effective, viable and technically sound alternative. Therefore, this research sought to investigate the influence of owners’ demographic and ownership information of Micro and Small Medium sized Enterprises (MSMEs)in explaining their credit default risk using primary data collected from randomly selected 62 MSME borrowers from Trincomalee District of Sri Lanka. Owners’ demographics studied by gender, civil status, size of family, age and age group, ethnicity, education and mobility (the distance between lender and enterprise) of the owners’ of MSMEs under study. Ownership information was proxied by the information whether the business is of sole proprietorship or partnership or of any other type. This study contributes to the literature a novel concept of Loan Repayment Risk Matrix (LRRM) as a comprehensive framework to approach credit repayment risk/credit default risk. Chi-Square Test has been employed to examine the relationship between dependent and independent variables and where the independent variables take continuous values (in the case of mobility), the difference of mean is tested with one-way analysis of variance (ANOVA) with post hoc comparison using Turkey’s honestly significant difference (HSD) test. It has been found that owners’gender, age, education, language and mobility and ownership information are significantly correlating with loan default risk of MSMEs and statistically significant relationship could not be found with respect to civil status, ethnicity and family size. Journal of Management 2013 9(1): 1-15
Highlights
Lending to Micro and Small Medium sized Enterprises (MSMEs) is crucial for economic and social development on one hand, it is deemed to be highly riskier as lending decision on SME sector is characterized by higher asymmetry of information in developing economies on the other.Though asymmetric information between borrowers and lenders is a general feature of all credit markets around the globe, it is acute in SME segment as information assisting default prediction are not often adequately, reliably and fairly disclosed by the SMEs
All lending technologies are sought for prudent lending by predicting the possibility of credit repayment or defaults by borrowers
Except for identifying the relationship between the distance of the borrowing SME from lending institution and the repayment risk, the relationship between repayment risk and all such other independent valuables as Borrowers’ Gender, Age, Education, Ethnicity, Language, Civil Status, Family Size and Ownership has been tested using Chi-Square, that belong to the family of univariate analysis
Summary
Lending to Micro and Small Medium sized Enterprises (MSMEs) (the acronym SMEs and MSMEs have been interchangeably used in this study) is crucial for economic and social development on one hand, it is deemed to be highly riskier as lending decision on SME sector is characterized by higher asymmetry of information in developing economies on the other.Though asymmetric information between borrowers and lenders is a general feature of all credit markets around the globe, it is acute in SME segment as information assisting default prediction are not often adequately, reliably and fairly disclosed by the SMEs. Lending decisions of financial institutions are not characterized by just the demand of borrowers for credit but it is a matter of comprehensive investigation of potential clients’ credit repayment behaviors. All lending technologies are sought for prudent lending by predicting the possibility of credit repayment or defaults by borrowers
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