Abstract:
The emergence of underground economy which majorly deals with cash has led to the evolution
of another category of tax fraud method because this kind of businesses does not leave a trail of
any transaction making it easy to evade tax and conceal the practice. The study sought to
determine the effect of tax fraud mitigation strategies among large tax payers on revenue
collection in Kenya revenue authority. The study was guided by two specific objectives: to find
out the role of technology adoption and staff training in mitigation of fraud at Kenya Revenue
Authority. The study was anchored on the prospect theory and fraud triangle theory and
adopted a descriptive research design. The unit of analysis for the study was fraud investigation
unit at KRA. The study targeted 1540 fraud unit investigation officers in LTO Section. Purposive
sampling technique was used and a proportional sample size of 90 staff was used. The study
used questionnaires for primary data collection. The collected data was processed using SPSS version 21. A linear regression model was used to examine the effect of tax fraud mitigation
strategies among large tax payers on revenue collection in Kenya revenue authority at 95 %
degree of Confidence. Results were presented using tables and pie charts. The study
concluded that staff training and technology adoption had a positive and significant effect on tax
fraud mitigation among large taxpayers at KRA. The study recommends the management of
Kenya Revenue Authority to regularly hold awareness seminars on tax evasion and fraud. The
management should also provide customized training to their staff so as to ensure they have
know-how on the operation of I-tax systems. There is also a need to engage qualified personnel
with advance technological skills to combat fraud since it will lead to a significant mitigation on
tax fraud. The study also recommends the management of KRA to enhance the adoption of ICT
software to detect and mitigate fraud. There is also need for the management to ensure that
forensic data analysis is done using digital analytical tools to detect and combat fraud.
