Effectiveness of Risk Management Strategies on Performance of the Customs and Border Control Department in Kenya

Abstract

The recent increase in complexities and volumes of international trade, fueled by technological advances have revolutionized global trading practices. This has consequently significantly affected the way customs administrations carry out their responsibilities and organize their business operations. Specifically, risk management process helps Customs administrations to focus on priorities and decisions on deploying limited resources to deal with the areas of highest risk. However, in Kenya, though custom risk management practices application is deemed to provide a wide range of benefits for customs and traders, the effect on the performance of customs and border control is not yet well established and this study aimed at shedding more light into this. The purpose of the study was to determine the effects of risk management strategies on firm performance: a case of Customs and Border Control Department in Kenya. The specific research objectives were to determine the effect of cargo scanning, cargo tracking, customs intelligence and integrated system on performance of customs and border control in Kenya. The guiding theories were Risk Management Theory, Theory of Constraints and Attribution Theory. The population of the study entailed employees working at the C&BC department at the border points and data was collected using both primary means. This was collected using questionnaires. The data collected was analyzed using descriptive including means, percentage frequency and standard deviation as well as inferential analysis. The collected data was presented using tables and figures. From the correlation analysis, Cargo Scanning had a Pearson Correlation of 0.323 and a p-value of 0.000, Cargo Tracking System had a Pearson Correlation of 0.200 and a p-value of 0.001, Customs Intelligence had a Pearson Correlation of 0.14 and a p-value of 0.05 and Integrated System had a Pearson Correlation of 0.438 and a p-value of 0.000. The positive coefficient indicated by the variables imply that they have a positive effect on the performance of the customs department of KRA. In addition, from the regression analysis results, the coefficient of determination (Adjusted R 2 ) was 0.415 implying that that the regression could explain up to 41.5 percent of the variation in the performance. The study therefore concludes that custom risk management has significant effect on the performance of the customs department in Kenya. The study thus recommends that the KRA management should highly prioritize custom risk management practices among their key strategies. The study also recommends that the government to formulate minimum risk management standards to be met by the customs department of KRA. KRA is also recommended to map customs and other administrations’ needs on changes of their current control procedures and IT equipment. The custom department is further recommended to set the broadest scope and the greatest content for risk management systems as far as their national resources allow.