Lender characteristics influencing loan default by SMEs in Kitui Central Sub-County

Syomane, Sammy F.; Wachira, Kevin

dc.contributor.author	Syomane, Sammy F.
dc.contributor.author	Wachira, Kevin
dc.date.accessioned	2019-04-16T09:14:27Z
dc.date.available	2019-04-16T09:14:27Z
dc.date.issued	2018
dc.identifier.citation	International Journal of Business Management and Economic Research(IJBMER), Vol 9(6), 1501-1509	en_US
dc.identifier.issn	2229-6247
dc.identifier.uri	https://www.ijbmer.com/docs/volumes/vol9issue6/ijbmer2018090606.pdf
dc.identifier.uri	http://repository.seku.ac.ke/handle/123456789/4424
dc.description.sponsorship	The Small and Medium Sized Enterprises (SMEs) are considered as the power driving many countries’ economies. It has been argued that SMEs are the lifeblood of most economies around the world and any government cannot afford to ignore the sector. Access to financial capital can be a critical factor for the success of SMEs, particularly in their early years. Commercial banks constitute the anchor of the growth of other sectors by providing them access to credit facilities in the form of loans. A recent Central Bank of Kenya (CBK) survey shows these SMEs topped the list of biggest loan defaulters in the first quarter of 2015. The objective of this study was to assess the lender factors influencing loan default by the SMEs operating in Kitui Central Sub-county. It is an extension of empirical work on the loan default. This study investigated two lender factors; the structure of interest rate and mode of loan repayment. The study targeted all the registered SMEs operating in Kitui Central Sub-County. This study adopted simple random sampling method to select 20% of the registered 407 SMSEs in Kitui Central Sub-County. Primary data was obtained by use of a structured questionnaire which was administered to the Chief Executive Officers of each specific enterprise. The data was edited, coded and analyzed using statistical package for social sciences (SPSS). Descriptive analysis was done and the respective statistics computed. Inferential statistics were also performed; multiple correlations and regression analysis. The correlation was used to investigate the association between the variables under study. Multiple regression analysis was used to measure the effect of lender factors on loan default by SMEs. The findings of this study revealed that there was a medium positive correlation and a significant relationship at 99% confidence level between the mode of loan payment and loan default (r=0.644, p=0.000). There was also a strong positive correlation and a significant relationship at 99% confidence level between the structure of interest rate and loan default (r=0.774, p=0.000). The mode of loan repayment and the structure of interest rate highly influenced loan default. The study recommends that the Lenders in Kitui Central Sub-County should revise their lending policies so that they can reduce loan repayment problems arising from the two lender characteristics investigated.	en_US
dc.language.iso	en	en_US
dc.title	Lender characteristics influencing loan default by SMEs in Kitui Central Sub-County	en_US
dc.type	Article	en_US