The Challenge
A large section of Indian low-income people depends upon informal sources to borrow small amounts (₹20,000 to ₹50,000) as working capital for their nano-enterprises. They are charged interest rates (IR) varying between 36% to 60% per year. Over the last couple of decades, microfinance companies and NBFCs have emerged as formal financing structures for this segment and have reduced the interest rates to about 25%. Yet this is still too high for any venture to become sustainable.
The high-interest rates are a result of the cost of financing, cost of risk, and cost of operations. For small loans today, the cost of risk and cost of operations (including follow-up for collection) itself amounts to about 12% or even more. This model works well when an experienced microfinance agent personally visits the home of the woman seeking a loan, interacts with her, and makes all kinds of queries for about 10 to 15 minutes to figure out the risk. Similar effort is required in follow-up, especially when the woman defaults.
Can we use AI and communications to digitize this journey?