Taxes and Finance Field Using Machine Learning Techniques: A Survey

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.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-17
DOI
https://doi.org/10.5281/zenodo.14506648
Primary Topic
Imbalanced Data Classification Techniques
Type
article
Field-Weighted Citation Impact
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article

Taxes and Finance Field Using Machine Learning Techniques: A Survey

Zenodo (CERN European Organization for Nuclear Research)
Imbalanced Data Classification Techniques
article

Taxes and Finance Field Using Machine Learning Techniques: A Survey

article en

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.

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Openalex Percentile: Top 59%
Imbalanced Data Classification Techniques
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