Influence of socio-demographic, behavioral and economic determinants on credit cards default risk in commercial banks in Kenya
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Date
2014-09-25
Authors
Kiarie, Francis Kanyi
Journal Title
Journal ISSN
Volume Title
Publisher
Kenyatta University
Abstract
Commercial banks playa major role in economic growth and development through provision
of credit to execute economic activities. Credit cards are financial payment instruments that
are increasingly accepted and used in consumer credit market worldwide. However, credit
card performance surveys shows that credit default is a major risk faced by commercial
banks in Kenya. The risk attributable to credit card default leads to high effective borrowing
rates and therefore increased cost of doing business. Mitigation against this risk is necessary
for the safety and soundness of the banking sector. This study aims to investigate the
influence of socio-demographic, behavioural and economic factors associated with credit
card holders on credit card default risks among credit card issuing commercial banks in
Kenya. The study proposes to use secondary data containing socio-demographic, behavioural
and economic details about credit card holders obtained from bank records. The target
population of the study will be all the credit card holders of the eighteen credit cards issuing
banks in Kenya. The study proposes to use a combination of cross-sectional and descriptive
research designs. Commercial banks issuing credit cards will be stratified as national and
multinational. From each stratum, simple random sampling will be applied to select sample
elements. Forward stepwise selection will be applied to obtain optimal set of explanatory
variables for the response variable. A Logistic regression model will then be fitted to
determine factors with high predictive power of default in credit card loans
Description
A Thesis Submitted to the School of Business in Fulfilment of the Requirements for the Award of Degree of Doctor of Philosophy in Business (Management Science) of
Kenyatta University, October, 2015
Keywords
Credit cards,, Credit risk,, Logistic model,, Logit transformation,, parameter estimation.