EFL uses the latest concepts in psychometrics and alternative data sources to assess creditworthiness of “thin file” or “no file” consumers and small businesses, unlocking individual potential through capital and expanding access to finance globally.
Borrowers in emerging markets seek more, better and faster access to credit, but they often do not have the required traditional credit history or collateral. Lenders want to serve more of these applicants, but they lack reliable data to predict credit risk. By collecting and analyzing nontraditional information about entrepreneurs and consumers, EFL aims to provide financial institutions with a more complete and accurate understanding of risk and opportunity.
EFL’s credit scoring algorithms measure something that all borrowers have: ability and willingness to repay. By analyzing behavioral patterns, character traits, geo-location data, and other nontraditional data, the EFL tool develops a deeper and more quantitative understanding of risk.