Abstract:
As in most economies worldwide, commercial banks are crucial in the Kenyan economy.
Their importance stems from the various functions and services they provide, which
contribute to economic growth, financial stability, and the country's overall
development. In Kenya, the Government aspires to achieve an economic growth rate
(GDP) of 10% p.a., as enshrined in Vision 2030 and beyond, which can only happen
in a stable financial economy. Equally, the attainment of the Kenya Kwanza Bottom-
3
Up Economic Transformation Agenda (BETA) plan is also dependent on a robust
financial sector. In 2022, the commercial banks in Kenya contributed approximately
Kes. (Million) 13,368,340, about 5% of the Gross Domestic Product in Kenya. A vibrant
banking sector depends on good loan performance, the primary source of bank income.
Sound loan performance enables banks to maintain adequate capital reserves, meet
operational expenses, and provide essential financial services. However, loan
performance has deteriorated over the last decade from a ratio of non-performing loans
to gross loans of 4.96% in 2013 to 14.5 % in June 2023. The gross non-performing
loans stood at Kes 541 billion by June 2023. The risk categorization indicated a
deterioration of 41 billion from December 2022 to June 2023. This is a cause of great
concern for the sustainability of commercial banks in Kenya. This study aimed to analyze
the combined influence of the selected predatory loan practices (borrower, lender, and
loan processing practices) on loan performance among commercial banks in Kenya. The
study adopted a positivist research philosophy and a descriptive research design.
The sampling frame and unit of analysis were the 39 commercial banks in Kenya
(CBK,2022). The unit of response was 234 managers of these 39 commercial banks. A
closed-ended questionnaire and a secondary data collection sheet were used to collect
data for the prediction. A pilot test was carried out to assess the instrument's internal
consistency using managers of three Micro Finance Banks in Nairobi, Kenya. Further,
Confirmatory Factor Analysis (CFA) was utilized to enhance construct validity by
generating the Kaiser-Meyer-Olkin coefficient and Bartlett’s Chi-square for factorability
analysis. Total variance explained scree plot and rotated component matrix were
generated and further interpreted. After testing the data for Gaussian distribution,
linearity, and autocorrelation, simple linear regression was used for inferential analysis.
The study found that the three (3) predictors, borrower practices, lender practices, and
loan processing practices, respectively, jointly explained approximately 58.5% of the
variations of loan performance among commercial banks in Kenya. Borrower practices
and lender practices were found to have a positive and statistically significant influence
on the loan performance of commercial banks in Kenya. Loan processing practices were
found to have a positive but no statistically significant influence on the loan
performance of commercial banks in Kenya. For borrower practices, the study
recommended that commercial banks review the borrower-driven predatory loan
practices leading to weak loan performance and incorporate them in the Know Your
Customer (KYC) tool for loan evaluation(s) and pricing. The interventions include
assessing the borrower's financial literacy, providing financial counselling services, and
strengthening loan processing practices within the banks. For lender practices, the study
recommended that commercial banks review or develop a profiling tool that identifies
customers who have been on loan without a break, a customer who might need
financial counselling, analyze the possibility of managing loan appetite for customers
with questionable ability to repay, reevaluate certain products associated with relatively
higher default rates, review policy on recharging securities successively and allow
potential borrowers to review all the loan terms and conditions before loan award.