Predicting risk of credit default using discriminant aproach:A study of tribal dairy darmers from Jharkhand

The study has identified the factors that discriminate defaulters from non-defaulters in the credit market using the survey data from 240 households. A discriminant function was employed to examine the relative importance of different socio-economic factors making borrowers to default. The magnitude of coefficient of the function is an indicator of the relative importance of individual variable. The study has suggested that higher per-capita income from crop production (38.72%), higher per-capita income from dairying (31.62%), percentage of expenditure in total income (16.87%), off-farm income sources (6.43%) and more earning adults in the family (6.36%) are the important factors to make the borrowers non-defaulters and vice versa for defaulters. Further, the confusion matrix of the derived classification analysis has cross-verified the predicted variable and has found the group classified correctly by 68.3 per cent. Hence, the model can be regarded to be valid in predicting a defaulter precisely based on the localized social factors. The study will help in addressing the concern of the credit institutions in assessing the credit risk capital and risk adjusted outcome for serving a larger group of smallholders community.