Synopsis:
Access to finance remains a persistent barrier for women-owned and informal SMEs across emerging markets. Traditional credit scoring methods often exclude first-time borrowers, informal workers, or entrepreneurs - disproportionately women - due to lack of collateral or formal financial histories. However, a new generation of fintechs is using AI-powered credit scoring models and alternative data - such as mobile money, transaction history, utility bills, and behavioral indicators - to assess creditworthiness more inclusively. This panel built on a recent IFC scan of the global landscape of alternative credit scoring models, coupled with borrower-level data analysis, to explore gender-differentiated outcomes and examine how the use of AI and non-traditional data expanded credit access and changed how financial institutions provided credit for women-owned MSMEs.
The session explored how these models worked in practice, what challenges remained, and what policy, infrastructure, or partnerships could help scale their impact - especially to reach more informal businesses.
Speakers:
Meghan McCormick, Co-founder & Chief Executive Officer, Oze
Munir Duri, Founder & Chief Executive Officer, Kifiya
Natasha Jethanandani, Co-founder & CTO, Kaleidofin
Moderator:
Namita Datta, Principal Economist, International Finance Corporation