Using Data Analytics to Optimize Multinational Corporate Tax Strategies
This paper examined the application of data analytics in optimizing multinational corporate tax strategies in an era of increasing regulatory complexity and transparency requirements. As global tax regulations evolve rapidly, multinational enterprises (MNEs) face unprecedented challenges in maintaining tax-efficient structures while ensuring compliance across multiple jurisdictions. Through analysis of current practices, regulatory frameworks, and emerging technologies, this study demonstrates how advanced data analytics can enhance tax planning, risk management, and compliance processes. The research revealed that organizations leveraging sophisticated analytics tools achieve significant improvements in tax efficiency, reduced compliance costs, and enhanced regulatory adherence. However, implementation challenges such as data quality, integration complexity, and ethical considerations must be carefully addressed. This paper provides a comprehensive framework for implementing data-driven tax strategies and maintaining regulatory compliance and corporate responsibility standards.
Institutions
- University of Ulster (GB)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-08-25
- DOI
- https://doi.org/10.5281/zenodo.16949337
- Primary Topic
- Geochemistry and Geologic Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.00