Artificial Intelligence and SME Credit Risk Assessment Under Information Asymmetry: Evidence from Morocco’s Conventional Banking Sector

This study examines how banking professionals in Morocco perceive the role of artificial intelligence (AI) in assessing the credit risk of small and medium-sized enterprises (SMEs). Based on a survey of 300 banking professionals, it explores whether perceptions of AI’s analytical capabilities, its limitations, information asymmetry, borrower behavioral uncertainty, and SME financing constraints are related to the perceived improvement in credit risk assessment. The study uses descriptive statistics, factor analysis, and generalized ordered logistic regression. The results show that banking professionals recognize AI’s potential to process information, identify risks, and support credit analysis, but their overall views of its contribution remain cautious. Professionals who have more positive perceptions of AI’s analytical capabilities tend to believe more strongly that it can improve credit risk assessment. Conversely, those who perceive greater limitations tend to be less convinced of its contribution. Both relationships are statistically significant. However, the results do not show a clear relationship between perceived information asymmetry and the perceived contribution of AI. Similarly, perceived borrower behavioral uncertainty and financing constraints are not significantly associated with this assessment. Overall, the findings show that banking professionals recognize the potential benefits of AI while remaining cautious about its contribution to SME credit risk assessment.