Machine Learning for Real-Time Credit Risk Assessment in Moroccan SME Lending

Small and Medium Enterprises (SMEs) constitute the backbone of Morocco's economy, representing 99.6% of the country's economic fabric according to the Moroccan MSME Observatory (OMTPME).Despite their critical role in generating 40% of GDP and employing 73% of the declared workforce, these enterprises face persistent barriers to credit access.With only 21% of Moroccan SMEs having access to a line of credit and a staggering financing gap estimated at $14 billion (13.5% of GDP) by the International Finance Corporation, traditional credit assessment methods have proven insufficient.This research proposes an advanced machine learning framework specifically tailored to the Moroccan SME context, leveraging alternative data sources and real-time risk assessment to address information asymmetry challenges while reducing bias in lending decisions.