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Leveraging Artificial Intelligence to Enhance Documentation Management and Transfer Pricing Compliance in Multinational Corporations: A Strategic Sustainability Perspective

多国籍企業における文書管理と移転価格コンプライアンスの強化のための人工知能の活用:戦略的サステナビリティの視点 (AI 翻訳)

Marius Boiță, Luminita Paiusan, Horatiu Soim, Florin Dumiter, Gheorghe Pribeanu, Ionela - Mihaela Milutin

Crossrefプレプリント2025-06-10#その他Origin: EU
DOI: 10.20944/preprints202506.0845.v1
原典: https://doi.org/10.20944/preprints202506.0845.v1

🤖 gxceed AI 要約

日本語

本論文は、多国籍企業における移転価格文書管理にAI(NLP、RPA、機械学習)を活用する可能性を探る。欧州多国籍企業OMEGAグループの事例研究に基づき、AI導入が人為的エラー削減、データ処理迅速化、OECD・EU規制への適合性向上に寄与することを示す。さらに、CSRDなどのESG要件への対応や紙ベースプロセスの削減によるサステナビリティ貢献にも言及する。

English

This paper explores the use of AI (NLP, RPA, ML) to enhance transfer pricing documentation for multinational corporations. Based on a case study of OMEGA Group, it finds that AI reduces errors, accelerates data processing, and improves compliance with OECD and EU regulations. It also addresses CSRD and ESG requirements, highlighting sustainability benefits from reduced paper use.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

日本でも移転価格税制の厳格化が進んでおり、AIによる文書管理自動化は実務上の関心が高い。CSRDへの対応はEU域外企業にも影響するため、日本企業のグローバル展開において示唆に富む。

In the global GX context

This paper bridges AI, tax compliance, and sustainability disclosure, relevant as CSRD expands globally. It offers insights for firms facing digital tax documentation demands, though its direct decarbonization link is weak.

👥 読者別の含意

🔬研究者:AIによる税務コンプライアンスとサステナビリティ開示の接点を探る研究として参考になる。

🏢実務担当者:移転価格文書の効率化とCSRD対応を同時に検討する企業の実務担当者に有用。

🏛政策担当者:AIを活用した税務コンプライアンスの国際基準策定における示唆を提供する。

📄 Abstract(原文)

In the context of growing global pressure for tax transparency and digital transformation, multinational corporations face increasing challenges in managing documentation and ensuring compliance with transfer pricing regulations. This paper explores how Artificial Intelligence (AI) technologies—specifically Natural Language Processing (NLP), Robotic Process Automation (RPA), and machine learning—can enhance the efficiency, accuracy, and traceability of documentation processes related to intercompany transactions. Based on a qualitative analysis and a case study of OMEGA Group, a large European multinational, we identify critical opportunities and limitations in the implementation of AI tools for fiscal reporting and documentation management. Our findings reveal that the integration of AI-driven systems significantly reduces human error, accelerates data processing, and improves alignment with OECD and EU regulatory standards. Moreover, we highlight how strategic investment in digital compliance infrastructures contributes to broader organizational sustainability by reducing operational risk and enhancing institutional credibility. In addition, this study considers the legal and regulatory implications of using AI for fiscal documentation, emphasizing the importance of algorithmic transparency and explainability (XAI) in jurisdictions with high formalism. Furthermore, the paper addresses emerging ESG requirements, particularly the EU’s Corporate Sustainability Reporting Directive (CSRD), and how AI supports sustainability-related disclosure by reducing paper-based processes and improving traceability. We also propose the inclusion of fiscal benchmarking mechanisms into AI systems to improve proactive risk assessment and cross-border compliance harmonization. The study concludes with practical recommendations for corporate decision-makers and public authorities aiming to improve tax governance through intelligent automation. It contributes to the growing body of literature on digital sustainability and offers a timely and original perspective on the intersection of technology, fiscal compliance, and responsible international management.

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