Authors : Abeer A Shujaaddeen; Fadl Mutaher Ba-Alwi; Abdulkader M. Al-Badani

Volume/Issue : Volume 9 - 2024, Issue 11 - November

Google Scholar : https://tinyurl.com/mrxud3rx

Scribd : https://tinyurl.com/mv3hvpej

DOI : https://doi.org/10.5281/zenodo.14506648

Abstract : Taxes are considered one of the most important revenues for developed and undeveloped countries alike, because of their importance in raising the level of the country. Taxes are an amount that the state imposes on companies and individuals. However many taxpayers try to evade tax by not paying their taxes in several ways, such as lying on the declaration form, hiding part of the data for tax fraud, and other ways and methods. Therefore, many countries have implemented many procedures and regulations to reduce tax evasion. Recently, it has resorted to artificial intelligence techniques such as machine learning (ML) and deep learning (DL) such as neural networks, decision trees, random forests, clustering techniques such as K-Mean, and others to reduce tax evasion. In this paper, we will present a summary of a group of countries in their trying to detect tax and financial evasion and fraud.

Keywords : Taxes, Tax Fraud, Taxpayers, Machine Learning, and Deep Learning.

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