arXiv:2605.26984v1 Announce Type: new Abstract: Tax evasion causes severe losses of government revenues and disturbs the economic order of fair competition. To help alleviate this problem, the latest tax evasion detection solutions utilize expert knowledge to extract features and then train classifiers to determine whether a company is suspected of tax evasion. However, existing solutions mainly focus on the statistical features of the company, but fail to exploit the rich interactive information in tax scenarios, which affect the detection performance. In this paper, we first model the tax sc
The increasing sophistication of AI and graph neural networks is enabling new applications in complex data analysis, making tax evasion detection a prime candidate for innovation.
Advanced AI tools for tax evasion detection can significantly improve government revenue collection and ensure fairer competition, impacting fiscal policy and corporate compliance.
Tax evasion detection methods can move beyond statistical features to exploit rich interactive information within tax scenarios, leading to more effective and targeted enforcement.
- · Government tax authorities
- · Tax compliant businesses
- · AI/ML solution providers
- · Companies engaged in tax evasion
- · Tax evasion consultants
More efficient and accurate identification of tax evasion schemes utilizing AI on heterogeneous graphs.
Increased government tax revenues leading to potential changes in public spending or reduced deficits.
Deterrence of tax evasion due to higher detection probabilities, fostering a more equitable economic environment.
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