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dc.contributor.authorKipchoge, Edwin Kibet
dc.contributor.authorMutuku, Morrison
dc.date.accessioned2024-03-19T07:55:40Z
dc.date.available2024-03-19T07:55:40Z
dc.date.issued2024-03
dc.identifier.citationKipchoge, E. K., & Mutuku, M. (2024). MOBILE BANKING AND FINANCIAL PERFORMANCE OF MICROFINANCE BANKS IN NAIROBI CITY COUNTY, KENYA. International Research Journal of Economics and Finance, 6(1).en_US
dc.identifier.urihttps://irjp.org/index.php/IRJEF/article/view/250/249
dc.identifier.urihttps://ir-library.ku.ac.ke/handle/123456789/27751
dc.descriptionArticleen_US
dc.description.abstractMicrofinance banks play an essential role in poverty reduction and economic development as they enhance financial inclusion. To reduce the cost of service delivery and improve efficiency in service delivery, microfinance banks in Kenya have adopted mobile payments. Despite adoption of mobile banking as among microfinance institutions in Kenya, their performance has been fluctuating over the years. Therefore, this study examined influence of mobile banking on microfinance institutions’ financial performance in Kenya. The study utilized an explanatory research design. The target population was 13 microfinance banks operating in Kenya and covered a period of 10 years (2012 to 2021). Since the sample size of the research was small, a census approach was employed. Secondary data on mobile banking and financial performance (ROA) was gathered from the Central Bank of Kenya and from microfinance banks’ financial statements in Kenya. Secondary data was gathered using data extraction checklist. Secondary data in this study was quantitative (continuous data). Quantitative data was also edited and then coded and keyed into STATA version 14 for purposes of analysis. Panel data analysis techniques were used in data analysis. Specifically, inferential and descriptive statistics were employed in quantitative data analysis. Descriptive statistics utilized included frequency distributions, percentages, standard deviation and mean. Diagnostic tests included autocorrelation test, normality test, heteroscedasticity test, linear test, nit root test and Hausman test. Regression analysis was utilized to examine the effect of independent variable on the dependent variable. The study found that mobile banking has a positive and significant relationship on financial performance of microfinance banks in Kenya. The study recommends that microfinance banks in Kenya should consider expanding their mobile banking services to reach a broader customer base. This could involve developing user-friendly mobile apps, SMS-based services, or other mobile banking channels to make it easier for customers to access their accounts and conduct transactions.en_US
dc.language.isoenen_US
dc.publisherIRJPen_US
dc.subjectMobile Bankingen_US
dc.subjectMicrofinance Banksen_US
dc.subjectFinancial Performanceen_US
dc.titleMobile Banking and Financial Performance of Microfinance Banks in Nairobi City County, Kenyaen_US
dc.typeArticleen_US


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