Over the years DFI’s have faced a number of criticisms. The low interest rates charged by DFI’s led to negative interest rates when the interest rate charged to borrowers was lower than the infla

Over the years DFI’s have faced a number of criticisms. The low interest rates charged by DFI’s led to negative interest rates when the interest rate charged to borrowers was lower than the inflation rate. The negative real interest rate then created excess demand for loans leading to allocation of loan to non-viable projects. Further loans were extended to social targets and politically favoured clients whose ideas may not have been the most viable. This led to high default rates and low rate of people seeking out a second loan after the first. The fact that DFI’s were state owned led to pressure on the government to forgive loans just before elections, to privilege the powerful with access to cheap funds meant for the poor, and to remove incentives for management to build tight, efficient institutions. The bulk of these weaknesses highly affect the financial performance of DFI’s and an efficient credit policy is able to mitigate the risks presented by these weaknesses. This study therefore sought to establish the effect of credit policy on financial performance of development finance institutions in Kenya. The study is of benefit to these finance institutions, loan seekers to make optimal decisions when choosing a source of finance and to the future researchers who will need information on credit policy and financial performance. The study adopted exploratory and descriptive survey research to identify the effects of credit policy on performance of DFI’s. Five Development Finance Institutions in Kenya were chosen. These are Industrial and Commercial Development Corporation (ICDC), Kenya Industrial Estates (KIE), Agricultural Finance Corporation (AFC), Industrial Development Bank Capital Limited (IDB) and Tourism Finance Corporation (TFC). The data was collected from credit risk managers of the various institutions. This is because they have the hands on knowledge on all credit policies in the institutions. Secondary sources for a period of 10 years, (2005-2015). Data analysis was based on the secondary data collected in this study. SPSS and Excel programs were used in cleaning of the data and running the analysis. Descriptive statistics was undertaken then correlation and regression analysis. The study found out that the regression model was found to predict 85.5% of the total variation in ROA as indicated by R square. This implies that the model can be used to predict 85.5% ROA while 14.5% is explained by other factors. The coefficient analysis found out that credit terms and collection efforts had negative contribution to ROA. However their effect wa insignificant. Credit standards and capital adequacy had a positive and significant effect on ROA at 95% confidence level. The study therefore concluded that, credit policy has significant effect on financial performance. It was recommended that the management of these institutions should develop sound credit policies which will help the institutions foster an increased financial performance. Further study can be done to determine the implementation process and challenges faced in implementing credit policies in development finance institutions.

Over the years DFI’s have faced a number of criticisms. The low interest rates charged by DFI’s led to negative interest rates when the interest rate charged to borrowers was lower than the inflation rate. The negative real interest rate then created excess demand for loans leading to allocation of loan to non-viable projects. Further loans were extended to social targets and politically favoured clients whose ideas may not have been the most viable. This led to high default rates and low rate of people seeking out a second loan after the first. The fact that DFI’s were state owned led to pressure on the government to forgive loans just before elections, to privilege the powerful with access to cheap funds meant for the poor, and to remove incentives for management to build tight, efficient institutions. The bulk of these weaknesses highly affect the financial performance of DFI’s and an efficient credit policy is able to mitigate the risks presented by these weaknesses. This study therefore sought to establish the effect of credit policy on financial performance of development finance institutions in Kenya. The study is of benefit to these finance institutions, loan seekers to make optimal decisions when choosing a source of finance and to the future researchers who will need information on credit policy and financial performance. The study adopted exploratory and descriptive survey research to identify the effects of credit policy on performance of DFI’s. Five Development Finance Institutions in Kenya were chosen. These are Industrial and Commercial Development Corporation (ICDC), Kenya Industrial Estates (KIE), Agricultural Finance Corporation (AFC), Industrial Development Bank Capital Limited (IDB) and Tourism Finance Corporation (TFC). The data was collected from credit risk managers of the various institutions. This is because they have the hands on knowledge on all credit policies in the institutions. Secondary sources for a period of 10 years, (2005-2015). Data analysis was based on the secondary data collected in this study. SPSS and Excel programs were used in cleaning of the data and running the analysis. Descriptive statistics was undertaken then correlation and regression analysis. The study found out that the regression model was found to predict 85.5% of the total variation in ROA as indicated by R square. This implies that the model can be used to predict 85.5% ROA while 14.5% is explained by other factors. The coefficient analysis found out that credit terms and collection efforts had negative contribution to ROA. However their effect wa insignificant. Credit standards and capital adequacy had a positive and significant effect on ROA at 95% confidence level. The study therefore concluded that, credit policy has significant effect on financial performance. It was recommended that the management of these institutions should develop sound credit policies which will help the institutions foster an increased financial performance. Further study can be done to determine the implementation process and challenges faced in implementing credit policies in development finance institutions.

Over the years DFI’s have faced a number of criticisms. The low interest rates charged by DFI’s led to negative interest rates when the interest rate charged to borrowers was lower than the inflation rate. The negative real interest rate then created excess demand for loans leading to allocation of loan to non-viable projects. Further loans were extended to social targets and politically favoured clients whose ideas may not have been the most viable. This led to high default rates and low rate of people seeking out a second loan after the first. The fact that DFI’s were state owned led to pressure on the government to forgive loans just before elections, to privilege the powerful with access to cheap funds meant for the poor, and to remove incentives for management to build tight, efficient institutions. The bulk of these weaknesses highly affect the financial performance of DFI’s and an efficient credit policy is able to mitigate the risks presented by these weaknesses. This study therefore sought to establish the effect of credit policy on financial performance of development finance institutions in Kenya. The study is of benefit to these finance institutions, loan seekers to make optimal decisions when choosing a source of finance and to the future researchers who will need information on credit policy and financial performance. The study adopted exploratory and descriptive survey research to identify the effects of credit policy on performance of DFI’s. Five Development Finance Institutions in Kenya were chosen. These are Industrial and Commercial Development Corporation (ICDC), Kenya Industrial Estates (KIE), Agricultural Finance Corporation (AFC), Industrial Development Bank Capital Limited (IDB) and Tourism Finance Corporation (TFC). The data was collected from credit risk managers of the various institutions. This is because they have the hands on knowledge on all credit policies in the institutions. Secondary sources for a period of 10 years, (2005-2015). Data analysis was based on the secondary data collected in this study. SPSS and Excel programs were used in cleaning of the data and running the analysis. Descriptive statistics was undertaken then correlation and regression analysis. The study found out that the regression model was found to predict 85.5% of the total variation in ROA as indicated by R square. This implies that the model can be used to predict 85.5% ROA while 14.5% is explained by other factors. The coefficient analysis found out that credit terms and collection efforts had negative contribution to ROA. However their effect wa insignificant. Credit standards and capital adequacy had a positive and significant effect on ROA at 95% confidence level. The study therefore concluded that, credit policy has significant effect on financial performance. It was recommended that the management of these institutions should develop sound credit policies which will help the institutions foster an increased financial performance. Further study can be done to determine the implementation process and challenges faced in implementing credit policies in development finance institutions.