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The Impact Of System Automation On Revenue Collection in Kenya Revenue Authority. (A Case Study of SIMBA)

Gitaru, Kelvin (2017): The Impact Of System Automation On Revenue Collection in Kenya Revenue Authority. (A Case Study of SIMBA). Published in:

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Abstract

The objective of the study was to examine the impact of system automation on revenue collection in Kenya revenue authority. This study employed descriptive study design. The study used secondary data collection. The study utilized KRA Customs data for ten financial years after Simba System.The data was analyzed using Gretl and presented in figures and tables. The study findings established that the number of transactions, increased significantly after the implementation process this means that due to revenue systems automation a high number of imported consignments were processed and passed through the centralized Document Processing Center (DPC). As a result of system, the shilling experienced a strong local currency then depreciated. The shilling has ever since been declining so sharply over the years against the US Dollar.This has a overall effect on the revenue collected in the sense that when the Kenyan shilling is weakened against the dollar i.e. one kshs trading for a very high value for the US dollar, the revenue collected will be of low value. The results established that the revenue collected was directly proportional to the exchange rates due to the positive sign in the coefficient. In conducting analysis of variance in the Gretl software, the probability value of p-value 2.6e-013 was obtained showing that the regression model was significant in predicting the relationship all the coefficients and revenue collected at 95% level of significance. The study findings established that there was a significant increase in the revenue collected after the automation to the simba system.The Exchange rates had an inverse effect on the revenue collected after the automation to the Simba system. The inflation rate was 10.5% in 2009 which increased to 15.2 in 2010 before slowing to 5.33% in 2011. This implies that the consumer price index in 2011 was 5.33. The study recommended that the ICT department should ensure that there is effective project coordination and change management for success of this automated system. Further, the department should ensure that there is a good data system and that is compatible with the system’s needs.

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