A credit gap of 56 per cent exists in the MSME (micro, small and medium enterprises) finance sector in India. While there is an estimated demand of ₹2,803,628 crore, the supply of finance stands at ₹1,038,948 crore, reveals a study conducted by US-based Entrepreneurial Finance Lab (EFL).
“In India, 92 per cent of MSMEs lack access to formal sector finance,” said EFL’s Asia Head Emily Silberstein.
Loaning to MSMEs is a costly affair for lenders because the processing of each application calls for intensive fieldwork and high levels of scrutiny, making the market under-penetrated. Nearly 50 per cent of the total application processing time is taken up in collecting the required documents. EFL is a global psychometric credit scoring company that began work in India in April 2013 and has helped domestic lenders, such as Janalakshmi Financial Services, Capital Float and an unnamed large private bank, assess loan applicants’ willingness to pay. The company has collected data across 15 States from over 10,000 entrepreneurs who had sought loans.
“One of the largest barriers to access to finance in India is the lack of detailed applicant credit histories or other documented metrics of credit worthiness. In a world increasingly dominated by data, lenders who leverage new non-traditional, quantifiable measures to assess applicants will be most successful,” said Silberstein.
Data collected by EFL suggest some tendencies toward bias in loan officers during their evaluation that is mostly subjective.
The bias rests on six main factors: familiarity with applicants, pressure to meet monthly quotas, banking history, residential stability, marital status, and age.
Preference for the familiar
Loan applicants applying in their hometowns are less likely to be rejected and receive better interest rates than their non-native counterparts.
For example, in Karnataka, Kannada speakers are 3.2 times more likely to receive credit than non-Kannada speakers; in Tamil Nadu, Tamil speakers are 5.8 times more likely to do so. However, Kannadigas and Tamilians are 1.3 times and 1.6 times, respectively, more likely to default on their loans in their respective States.
Marital status is taken into consideration because loan officers believe that spouses would bring in a second income, and therefore married applicants would be less risky than divorced or single ones. However, the data suggest that marital status has minimal impact on an applicant’s credit risk.
According to EFL’s data, one-third of loan officers over-report client revenues because they need to meet sales targets. Moreover, banks have historically overcome the information gap about the loan applicant by using labour intensive screening processes.
All this, coupled with the growing competition for skilled labour in the industry over the past six years, has resulted in loan officer salaries increasing 174 per cent.
This article was originally published in >The Hindu Business Line
