Default prediction models in micro finance: case study of Karnataka (India)

Abstract

The growth of Indian microfinance sustained through the liquidity crunch and continued at an increased rate in the second half of 2009. The Indian financial system, as a whole demonstrated its confidence in the Micro Finance Industry with more than 90 percent of the funding for micro finance in India coming from domestic channels. Micro Finance is one of the strategies for increasing financial inclusion in India. But, since loans are more freely available, the poor households tend to borrow beyond their means leading to higher default rates, which is a cause for concern. This paper attempts to build default prediction models Using Artificial Neural Networks, based on the demographic characteristics of the borrowers. It also identifies the demographic characteristics that play an important role in prediction and then rank them based on their importance in prediction