Lendingtech Startups Are Using AI, ML To Boost Financial Inclusion


Startups in India are using AI, ML, and data analytics to offer loans to underserved players in the micro, small, and medium enterprises (MSME) sector. The RBI estimates that the credit demand in the MSME space stands at $490 Bn, but the overall supply from formal sources is only $192 Bn, indicating how the sector remains underserved. Traditional lenders have left a gap that fintech startups are filling by assessing the creditworthiness of customers in alternative ways. However, fintech startups need to work on feedback loops and understand customer pain points to keep the credit quality and portfolio healthy.  Pallavi Shrivastava, co-founder of Progcap, emphasized the need for lendingtech startups to focus on feedback loops and understanding customer pain points as areas for improvement. She explained that it is not enough to rely solely on data and underwriting to make lending decisions, but also to engage with customers to ensure they understand the financial product being offered and the importance of repaying the loan in a timely manner. Additionally, feedback loops can help startups improve their lending decisions and keep their credit quality and portfolio healthy.

Fintech startups are using AI, ML, and data analytics to offer loans to underserved players in the key sectors of the country. This approach allows them to assess the creditworthiness of borrowers more accurately, without relying solely on traditional collateral-based loans. By analyzing a range of data points, including a borrower’s financial history, transactional data, and other factors, fintech startups can make faster and more informed lending decisions. This can be especially beneficial for small and medium-sized enterprises (SMEs) and individuals who may not have sufficient collateral to secure traditional bank loans.