Transfer Pricing in a Post-COVID World: Balancing Compliance with New Global Tax Regimes
Keywords:
Transfer pricing, COVID-19Abstract
The COVID-19 pandemic disrupted global economies, challenging multinational corporations to navigate complex transfer pricing regulations while balancing compliance with rapidly evolving tax regimes. As supply chains were restructured, profit margins recalibrated, and operational models adapted to new realities, traditional transfer pricing methodologies faced increased scrutiny from tax authorities worldwide. The pandemic accelerated discussions on equitable profit allocation, particularly for digital economy businesses, while new global frameworks such as the OECD’s Unified Approach gained momentum. Multinationals now face heightened risks of disputes as governments grapple with revenue shortfalls and intensify enforcement. In this environment, transfer pricing strategies must evolve beyond compliance to incorporate robust documentation, real-time data analytics, and proactive stakeholder communication. Companies must reassess intercompany transactions, pricing of intangibles, and the arm’s length principle within the context of pandemic-induced disruptions, such as market volatility and altered supply-demand dynamics. This paper explores how organizations can balance meeting compliance obligations and adapting to new global tax regimes. It highlights the importance of integrating risk management frameworks, leveraging advanced technology for tax reporting, and fostering collaboration with tax authorities to minimize disputes. Additionally, it examines case studies of industries most affected by the pandemic—such as pharmaceuticals and technology—to illustrate practical approaches for managing transfer pricing in a post-COVID world. By adopting a forward-looking, flexible approach, businesses can ensure compliance and build resilience in the face of ongoing regulatory changes and economic uncertainty.
Downloads
References
Megersa, K. (2020). Tax reforms after COVID-19 and financial crises. Knowledege, Evidence and learning for Development. Institute of Development studies. Helpdesk Report.
Michel, A. N. (2020). Post-COVID-19 Tax Policy: Keeping Taxes Low to Ensure a Robust Recovery. Heritage Foundation Backgrounder, (3549).
Kelsey, J., Bush, J., Montes, M., & Ndubai, J. (2020). How ‘Digital Trade’Rules Would Impede Taxation of the Digitalised Economy in the Global South. Third World Network.
Collins, M. (2017). Taxation: Measures and policy issues. The Economy of Ireland: Policy Making in a Global Context, 92-115.
POST, T. B. B. I. A., & EUROZONE, O. (2013). Policy Note.
Bhandari, B. (2006). Essays on Foreign Direct Investment and Income Inequality and Cross-price Effects in the US Trade Balance (Doctoral dissertation, University of Oregon).
Strategy, T. A. (2002). Ministry of Finance. Final Draft. January.
Qureshi, A. H., & Ziegler, A. (1999). International economic law (p. 338). London.
Crouch, C. (2009). Privatised Keynesianism: An unacknowledged policy regime. The British journal of politics and international relations, 11(3), 382-399.
Reid, J., Nicol, G., Burns, N., & Chanda, S. (2017). Long-term asset return study. The next financial crisis. London: Deutsche Bank.
Eichengreen, B., TOBIN, J., & WYPLOSZ, C. (2000). Financial Globalization. The Economic Journal, 105(428), 162-172.
Umeora, C. E. (2020). EFFECT OF CORONA VIRUS DISEASE (COVID 19) PANDEMIC ON OFFSHORE BANKING AND TAX HAVENS. www. accexgate. com, 1(3), 171-184.
Razin, A., Sadka, E., & Schwemmer, A. H. (2020). DEglobalizaion and Social Safety Nets in Post-Covid-19 Era: Textbook Macroeconomic Analysis (No. w27239). National Bureau of Economic Research.
Meyer, T. (2020). Trade law and supply chain regulation in a post-COVID-19 world. American Journal of International Law, 114(4), 637-646.
Enderwick, P., & Buckley, P. J. (2020). Rising regionalization: will the post-COVID-19 world see a retreat from globalization?. Transnational Corporations Journal, 27(2).
Thumburu, S. K. R. (2020). Enhancing Data Compliance in EDI Transactions. Innovative Computer Sciences Journal, 6(1).
Thumburu, S. K. R. (2020). Leveraging APIs in EDI Migration Projects. MZ Computing Journal, 1(1).
Gade, K. R. (2020). Data Mesh Architecture: A Scalable and Resilient Approach to Data Management. Innovative Computer Sciences Journal, 6(1).
Gade, K. R. (2020). Data Analytics: Data Privacy, Data Ethics, Data Monetization. MZ Computing Journal, 1(1).
Katari, A. Conflict Resolution Strategies in Financial Data Replication Systems.
Katari, A., & Rallabhandi, R. S. DELTA LAKE IN FINTECH: ENHANCING DATA LAKE RELIABILITY WITH ACID TRANSACTIONS.
Komandla, V. Enhancing Security and Fraud Prevention in Fintech: Comprehensive Strategies for Secure Online Account Opening.
Komandla, V. Transforming Financial Interactions: Best Practices for Mobile Banking App Design and Functionality to Boost User Engagement and Satisfaction.
Gade, K. R. (2019). Data Migration Strategies for Large-Scale Projects in the Cloud for Fintech. Innovative Computer Sciences Journal, 5(1).
Immaneni, J. (2020). Cloud Migration for Fintech: How Kubernetes Enables Multi-Cloud Success. Innovative Computer Sciences Journal, 6(1).
Boda, V. V. R., & Immaneni, J. (2019). Streamlining FinTech Operations: The Power of SysOps and Smart Automation. Innovative Computer Sciences Journal, 5(1).
Nookala, G., Gade, K. R., Dulam, N., & Thumburu, S. K. R. (2020). Automating ETL Processes in Modern Cloud Data Warehouses Using AI. MZ Computing Journal, 1(2).
Nookala, G., Gade, K. R., Dulam, N., & Thumburu, S. K. R. (2020). Data Virtualization as an Alternative to Traditional Data Warehousing: Use Cases and Challenges. Innovative Computer Sciences Journal, 6(1).
Muneer Ahmed Salamkar, and Karthik Allam. “Data Lakes Vs. Data Warehouses: Comparative Analysis on When to Use Each, With Case Studies Illustrating Successful Implementations”. Distributed Learning and Broad Applications in Scientific Research, vol. 5, Sept. 2019
Muneer Ahmed Salamkar. Data Modeling Best Practices: Techniques for Designing Adaptable Schemas That Enhance Performance and Usability. Distributed Learning and Broad Applications in Scientific Research, vol. 5, Dec. 2019
Muneer Ahmed Salamkar. Batch Vs. Stream Processing: In-Depth Comparison of Technologies, With Insights on Selecting the Right Approach for Specific Use Cases. Distributed Learning and Broad Applications in Scientific Research, vol. 6, Feb. 2020
Muneer Ahmed Salamkar, and Karthik Allam. Data Integration Techniques: Exploring Tools and Methodologies for Harmonizing Data across Diverse Systems and Sources. Distributed Learning and Broad Applications in Scientific Research, vol. 6, June 2020
Naresh Dulam, et al. “Data As a Product: How Data Mesh Is Decentralizing Data Architectures”. Distributed Learning and Broad Applications in Scientific Research, vol. 6, Apr. 2020
Naresh Dulam, et al. “Data Mesh in Practice: How Organizations Are Decentralizing Data Ownership ”. Distributed Learning and Broad Applications in Scientific Research, vol. 6, July 2020
Naresh Dulam, et al. “Kubernetes Operators: Automating Database Management in Big Data Systems”. Distributed Learning and Broad Applications in Scientific Research, vol. 5, Jan. 2019
Naresh Dulam, and Karthik Allam. “Snowflake Innovations: Expanding Beyond Data Warehousing ”. Distributed Learning and Broad Applications in Scientific Research, vol. 5, Apr. 2019
Sarbaree Mishra. A Distributed Training Approach to Scale Deep Learning to Massive Datasets. Distributed Learning and Broad Applications in Scientific Research, vol. 5, Jan. 2019
Sarbaree Mishra, et al. Training Models for the Enterprise - A Privacy Preserving Approach. Distributed Learning and Broad Applications in Scientific Research, vol. 5, Mar. 2019
Sarbaree Mishra. Distributed Data Warehouses - An Alternative Approach to Highly Performant Data Warehouses. Distributed Learning and Broad Applications in Scientific Research, vol. 5, May 2019
Sarbaree Mishra, et al. Improving the ETL Process through Declarative Transformation Languages. Distributed Learning and Broad Applications in Scientific Research, vol. 5, June 2019
Babulal Shaik. Network Isolation Techniques in Multi-Tenant EKS Clusters. Distributed Learning and Broad Applications in Scientific Research, vol. 6, July 2020