Can AI Uplift Entrepreneurs That Traditional Banks Reject? | Mercedes Bidart | TED

Quick Overview

Mercedes Bidart successfully developed AI models that leverage non-traditional data sources like text messages and social media activity to assess the creditworthiness of informal entrepreneurs in Latin America, enabling financial inclusion where traditional banking systems fail them due to lack of formal records.

Key Points: Bidart grew up in a family of small business owners in Argentina and chose to study political science instead of continuing the family business, eventually pursuing AI research at MIT focused on economic development. Traditional financial systems reject half of the Latin American population who are informal entrepreneurs because they lack formal credit history or bank accounts, making them invisible to conventional risk assessment models. Bidart and her team developed a system that uses non-traditional data—specifically text messages (Text Score) and social media presence (Social Score)—to create a financial identity for these entrepreneurs. The Text Score analyzes factors like bill payments, order confirmations, and mobile charges, while the Social Score evaluates online presence and engagement, allowing them to assess repayment probability. The resulting AI models can predict loan repayment metrics like amount, timing, and conditions, achieving accuracy levels above market standards (e.g., 0.83 vs. market standard) by analyzing this alternative data. This AI-driven approach allows for the offering of tailored financial services, such as loans, to those previously excluded by formal banking systems, proving that credit history can improve in months, not years. The core philosophy is that for AI to be fair, it must learn from everyone, not just those represented in existing, often biased, formal data sets.

Context: Mercedes Bidart, inspired by her family's small business background in Argentina and later her studies at MIT, addresses the critical problem of financial exclusion faced by informal entrepreneurs in Latin America. These small business owners, who collectively account for 99% of companies and one-third of the GDP in the region, are typically denied loans by traditional banks because they operate outside formal financial structures, lacking credit history or bank statements, rendering them 'invisible' to conventional risk assessment.