There has been a recent boom in the financial lending space in the last 3-4 years. Various NBFCs like MoneyTap, IndiaLends, Qbera, and Capital First are competing to grab the online urban market lending needs. However, there are still more than 60 million micro-enterprises in India that are claimed not to fit enough in order to get loans from the banks and the NBFCs. These micro-enterprises are not able to maintain a balance sheet enough to be attractive for lending. It has resulted in a big financial backing gap of more than Rs sixteen trillion(as approximated by IFC Report 2012) which continues to be unaddressed.

The burgeoning online lending segment in India is also giving rise to a new kind of challenge on sourcing credit score data. To solve this problem, several fintech companies are using Artificial Intelligence (AI) and Machine Learning (ML) to create alternate lending data score for more than 80 per cent of the Indian population who have no credit scores. From the place where people live to the restaurants they visit to their digital footprints on social media, ML captures it all. Mohan Yadav, a 25-year-old software professional in Mumbai, was denied a ₹25,000 personal loan by his bank since he had no credit history. After a quick search online, he applied for a loan from Cashe, a Mumbai-based fintech company that offers personal loans to salaried professionals who have just entered the workforce.