Customer characteristics and over-indebtedness in Kenya

Abstract

The influence of an individual’s characteristics on their financial decisions has always been an area of great interest to researchers. The use of customer characteristics to predict the decisions that a customer will make in regards to use of digital credit service, informed in part why this study was necessitated. Increased customer over-indebtedness has become a trend and a norm among the users of digital financing platforms. This study sought to ascertain the effect of customer characteristics on customer over-indebtedness. The survey research design was used. Stratified sampling was used to obtain a target sample size of 384 digital loan users in the informal sector of Nairobi City County. Pearson correlation coefficient (r) was used to determine the correlation between the two variables and in the hypothesis testing, binary logit was used for the analysis of results. From the findings, the null hypothesis that there was no significant effect of customer characteristics on customer over-indebtedness was rejected. The findings of the study, indicated that three factors of customer characteristics i.e., family status, academic achievement of a customer and the average monthly income all had a positive significant correlation with customer over-indebtedness. Family status i.e., whether a customer was married or not; was the strongest single factor that affected the model. The results showed that married people had a 2.57 times greater likelihood of being over-indebted compared to the single people. Other factors of characteristics like the gender of the customer, age group, and current occupation did not contribute significantly to the model though positively correlated to customer over-indebtedness