Factors influencing banks' financing decisions to small and medium enterprises (SMEs) in the agriculture sector (case study of Agribank, 2009 - 2012)

Abstract

A study was carried out to investigate factors that influence banks’ financing decisions to SMEs operation in the agriculture sector. The objective was to assess factors that influence credit rationing behaviour of banks involved in financing of SMEs in the agricultural sector since there is a ‘financial gap’ between banks and these SMEs. Literature was reviewed on factors that influence SME finance by banks that resulted in formulation of research hypotheses. The objective of literature review was to establish literature gaps on factors influencing bank financing decisions to SMEs and relate them to financing of agriculture SMEs. From literature it was found that there is much information that relate to challenges and motives of financing SMEs in the agriculture sector. A quantitative research was carried out using a case study of Agribank, a registered commercial bank that is involved in financing of agriculture. A self administered questionnaire was distributed to a sample drawn from relationship officers and branch manager within the bank’s northern region to collect data. Relationships between research variable were tested using various techniques that include Mann Whitney test, Kruskal – Wallis test, correlation and regression analysis. The results showed that there were statistically insignificant relationships between demographic characteristics of loan granting officers within the bank and loan approval decisions. There were also no statistically significant relationships between the independent variable (age of the SME, quality of information and administration costs) and the dependent variable (loan approval decisions by the bank). It was concluded that most of the identified factors had no statistically significant relationships with the loan approval decisions. The regression model was also fairly a poor one with an r2 value of 0.08. It was concluded that the model might be influenced to a larger extend by external factors that are specific to the Agribank and the country that include political interference and macroeconomic factors. It was recommended to consider the external factors into the model so as to improve its effectiveness in future studies.