Patterns and heterogeneity in credit repayment performance: Evidence from Malian farmers

Formal credit can enhance farmers' purchasing power, increase productivity, and enforce resilience throughout the agricultural sector. Therefore, analyzing bank clients and credit data in the agricultural sector is of interest. This study aims to (1) investigate distinct cluster patterns among the bank's farmer clients in Mali utilizing clustering techniques on 3335 farmer clients with 9469 credit records data collected between January 2010 and April 2022, and (2) reveal whether these clusters exhibit heterogeneity regarding credit repayment performance. Our results indicate the presence of three distinct clusters differing by personal and credit characteristics: frequent low-volume farmers (FLVF), moderate-volume high-interest farmers (MVHIF), and high-volume long-term farmers (HVLTF). Each identified and distinct cluster demonstrates a dissimilar on time, late, or defaulted repayment performance. The associations between credit volume, credit duration, interest rate, repayment periodicity, and various delayed repayments differ across clusters, indicating heterogeneity. Hence, tailored financial products to different farmer clusters are needed to enhance the repayment performance of farmers in Mali.