Sinha, R.K., Chattopadhyay, P., & Sourav, P. (2021).
Empirical Economics Letters.
Abstract
The growth of internet lending platforms has opened a great opportunity for micro-financing
companies and is acting as a viable alternative in the finance industry. The most common business
proposition in the internet-lending platform is Peer-to-Peer (P2P) lending platform. However, P2P
lending platforms have great chance of vulnerability because of the increase in non-performing
assets (NPAs) in recent times due to the lack of proficiency and expertise in finding out the
borrowers’ creditworthiness. Lack of government stringent rules and regulations has increased the
chances of credit failure in P2P lending platforms. This study offers a unique model for checking the
creditworthiness of borrowers based on analysis using Artificial Neural Networks (ANN). The results
specify that the ANN model for credit scoring is successful in finding out default loan applications as
well as provides smart decision-making for the lenders.
