Innovative solutions for tackling tax evasion and fraud: Harnessing blockchain technology and artificial intelligence for transparency
1 Independent Researcher, Lagos, Nigeria.
2 Imo State Internal Revenue Service, Nigeria.
3 Newcross Exploration and Production Limited, Nigeria.
Review
International Journal of Frontline Research in Multidisciplinary Studies, 2023, 02(01), 010–018.
Article DOI: 10.56355/ijfrms.2023.2.1.0035
Publication history:
Received on 19 November 2023; revised on 22 December 2023; accepted on 25 December 2023
Abstract:
Tax evasion and fraud are significant global challenges that undermine public finances, erode trust in tax systems, and exacerbate socioeconomic inequalities. Traditional methods for addressing these issues often fall short due to their inefficiencies and susceptibility to manipulation. This paper explores the transformative potential of blockchain technology and artificial intelligence (AI) in combating tax evasion and enhancing transparency in tax administration. Blockchain’s core features, such as decentralization, immutability, and real-time transaction tracking, offer innovative solutions for secure tax record management and fraud prevention. Similarly, AI’s capabilities in data analysis, pattern detection, and audit automation present new opportunities to identify and mitigate fraudulent activities. The paper also examines the challenges and ethical considerations associated with implementing these technologies, such as infrastructure demands, data privacy, and algorithmic bias. Recommendations are provided for policymakers, including modernizing tax infrastructure, fostering public-private partnerships, and promoting international cooperation. By leveraging blockchain and AI responsibly, tax authorities can revolutionize tax governance, enhance compliance, and rebuild public trust in taxation systems.
Keywords:
Tax evasion; Tax fraud; Blockchain technology; Artificial intelligence; Transparency in taxation; Tax system innovation
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Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0