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,

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... his 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 soleproprietorship 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.