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<p>The issue of tax evasion is relevant in many countries and its identification can be challenging. Companies belonging to groups tend to employ tax minimization strategies more frequently compared to individual companies. Therefore, the identification of interconnected company groups can aid in uncovering cases of tax avoidance. The aim of this research is to propose a methodology for utilizing big data to determine interconnected company groups and types of ownership structures, which would assist in identifying potential cases of tax evasion. Graph theory is applied for this purpose. The proposed approach for company selection, which combines methods from graph theory and statistical analysis, is designed to identify non-typical company groups with higher tax evasion risk and is applied in the context of an Eastern European Union country. This methodology’s main advantage lies in utilizing multi-layered graphs for identifying company groups, wherein the number and nature of connections can be expanded as needed.</p>

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Identification of the Company Groups in Assessing the Risk of Tax Evasion: A Graph Theory Approach

  • 期刊论文

  • 发表日期：

    2025年10月8日

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  • Tomas Ruzgas,
  • Alina Stundziene,
  • Rozita Susniene,
  • Mantas Lukauskas,
  • Egidijus Sinkevicius,
  • Ieva Staneviciute,
  • Jurgita Arnastauskaite Zenceviciene

摘要

The issue of tax evasion is relevant in many countries and its identification can be challenging. Companies belonging to groups tend to employ tax minimization strategies more frequently compared to individual companies. Therefore, the identification of interconnected company groups can aid in uncovering cases of tax avoidance. The aim of this research is to propose a methodology for utilizing big data to determine interconnected company groups and types of ownership structures, which would assist in identifying potential cases of tax evasion. Graph theory is applied for this purpose. The proposed approach for company selection, which combines methods from graph theory and statistical analysis, is designed to identify non-typical company groups with higher tax evasion risk and is applied in the context of an Eastern European Union country. This methodology’s main advantage lies in utilizing multi-layered graphs for identifying company groups, wherein the number and nature of connections can be expanded as needed.