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.
Key Words: Customer Characteristics, Customer Over-indebtedness, Behavioural Analysis,
Financial Literacy, Demographics.