Management Practice Insights

Abstract

Traditional lenders serve only a fraction of India's millions of small businesses. Conventional banks do not meet this massive demand for credit since their assessment methods do not apply to this segment. Regulations cause banks to exclude small businesses as they lack formal financial data filing. However, the lack of formal data does not mean that small businesses do not have a digital data footprint. In fact, small businesses generate data through mobile payments, utility bills, social media activity and digital transactions—these data points reveal credit worthiness that traditional scoring cannot work with. Recent research by Maximilian Tigges, Sonke Mestwerdt, Sebastian Tschirner and Rene Mauer demonstrates how AI and alternative data adoption reduce this frustrating information gap between lenders and borrowers.¹ Here is the critical insight: alternative data sources enable real-time creditworthiness assessment that works. This promising application of AI can potentially turbocharge the prosperity of small businesses. It can also significantly benefit fintech leaders, venture capitalists, and policymakers driving India's digital lending transformation.² It can also overcome the lack of geographical reach of traditional lenders. To successfully capitalise on this opportunity, fintech companies must resolve data quality issues, triangulate beyond single data sources, and tailor new financial products.