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dc.contributor.authorOtieno, Simeyo
dc.contributor.authorNyagol, Michael
dc.contributor.authorOnditi, Arvinlucy
dc.date.accessioned2020-11-26T12:33:19Z
dc.date.available2020-11-26T12:33:19Z
dc.date.issued2016
dc.identifier.issn2222-1697 (Paper)
dc.identifier.issn2222-2847 (Online)
dc.identifier.urihttp://ir.jooust.ac.ke:8080/xmlui/handle/123456789/8901
dc.description.abstractEffective Credit risk management enhances financial performance of Microfinance banks. A sound Microfinance banking subsector is vital for economic development as the sector supports low end entrepreneurs operating SMEs that form the bulk of Kenyan economy. In Kenya the microfinance banking subsector has been faced with risk management challenges. This necessitated the adoption of the Risk Based Supervision approach of supervising Microfinance banks in 2010. Additionally, CIS feature was extended to MFBs to check on credit default. Despite these efforts, most MFBs are recording negative growth even with increased number of Microfinance bank licences being granted. The level of profitability and sustainability of the sector dropped significantly with ROE and ROA reported at 8% and 1% respectively. Non-performing loans increased by 6.9 percent and Risk coverage ratio shows a worrying negative trend. Hence the major objective for this study was to establish the relationship between Credit risk management and financial performance of Microfinance banks in Kenya. Specific objectives were: to establish the relationship between Portfolio at risk (PAR) and performance of MFBs and to determine the relationship between loan loss Provision coverage ratio (LLPCR) and performance of MFBs. Longitudinal research design utilizing panel data covering the period from 2011 to 2015 was used. Target population comprised 12 licensed MFBs. Purposive sampling was used to obtain a sample of 6 MFBs. Document analysis guide was used to gather secondary quantitative data from the MFBs financial reports. Descriptive statistics were used to show the trend of MFB risk exposure and performance. Pearson correlation was used to determine strength and association among variables. Panel data analysis based on system GMM technique was used to estimate a multiple regression model and test for significance of relationship between Risk management and financial performance. The findings were that Credit risk management with PAR and LLPCR parameters had a strong negative correlation (r=-0.68), giving a significant negative relationship with both ROAA and ROAE performance measures as depicted by regression coefficient of -0.2 estimated by GMM. Thus, the study concluded the existence of a significant relationship Credit risk management and performance and that credit risk management impacts performance of MFBs. The study recommended that Credit managers should operate under a sound credit granting process with well-defined credit-granting criteria detailing the MFB’s target market, a thorough understanding of the borrower, purpose & structure of the credit, and its source of repayment.en_US
dc.language.isoenen_US
dc.publisherIISTEen_US
dc.subjectCredit risk,en_US
dc.subjectMicrofinance banksen_US
dc.subjectPerformanceen_US
dc.titleRelationship between Credit risk management and financial performance: empirical evidence from microfinance banks in Kenyaen_US
dc.typeArticleen_US


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