Abstract

ABSTRACT:

The small and medium enterprises are the pillars of economic development in India. With over 30 million units of SME units in India, they are contributing to 45% in country's GDP. The importance of SMEs in manufacturing is mainly due to the volume of units that exist in this category. Recently government has taken several steps in boosting the manufacturing in India, "Make in India" is one such initiative and National Manufacturing policy has been announced to revamp the sector. One of the major hindrances in expansion is lack of timely and sufficient funds. Today the total gap of SME funding is estimated to be approximately $126 billion. Out of which the debt gap is approximately $84 billion (Ravij Janjanan, 2014). Research is undertaken to know the determinants of credit in Mumbai city which is the financial capital of India. Present paper studied the determining factors of credit in SME sector in Mumbai by applying Binary logit regression model. Data was collected from supply side through administered questionnaire. Factors were identified through focus group interviews and later tested for validity and reliability.Net worth and Age of the owner found to be most impacting factors loan officers are considering while granting credit to SMEs in Mumbai. Study also found that age of the owner is very important determinant along with net worth and financial feasibility. Odds ratio for age of the owner (0.70) of respondents indicate that whose loans are approved belongs to lower age groups than the respondents whose loans are disapproved. Odds ratio for Net worth (1.36) of respondents indicate that one-unit change in the Net worth is going to increase the loan acceptance by 1.36 times. Managerial implications of this study would be Banks can focus on more startup loans and can tap young entrepreneurs who have creative and prospective ideas on business. SME owners should focus more on innovation, clarity of thought expressed in project proposal and approach for loan sanctions at young age to improve the credit flow.

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