Abstract

Credit assessment risk for small and medium enterprises (SMEs) offers special challenges to practitioners, regulators and academics. The lenders’ design of the package of credit to SMEs may affect the propensity to default or lead to delinquency. Considering the fundamental role being played by small-sized industries in Indian economy and emphasis on inclusive economy, we aim to develop a default prediction model, specifically for SMEs. Apart from the conventional ‘ability to pay’ basis of analyzing borrower-centric default risk, there may be a set of other explanatory variables that can be modelled to assess the credit default. The study here examines the behaviour of relevant measures of default risk and explores the most significant variables of the financial package to construct a model for SMEs by applying multinomial logistic regression technique. The study is based on database covering two years of the time period from 2007 to 2009 on 2,864 SMEs pertaining to an emerging cluster obtained from a prominent financial institution in Delhi.

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