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Technological Innovation and Sustainable Financial Reporting

技術革新と持続可能な財務報告 (AI 翻訳)

Ekwuye, Ben Madu, Lawal I. Lamidi, Okoroiwu, Kemdi Lugard, K. Ume

INTERNATIONAL JOURNAL OF SOCIAL SCIENCE HUMANITY & MANAGEMENT RESEARCH📚 査読済 / ジャーナル2026-01-31#AI×ESG経営インパクト: 資金調達対象セクター: finance
DOI: 10.58806/ijsshmr.2026.v5i1n17
原典: https://doi.org/10.58806/ijsshmr.2026.v5i1n17

🤖 gxceed AI 要約

日本語

本研究は、ブロックチェーン、AI、ビッグデータ、XBRLなどの技術が、ナイジェリアなどの新興市場における持続可能な財務報告に与える影響を検討する。ステークホルダー理論や技術受容モデルに基づき、ESGデータ収集の自動化や予測分析、統合監査の可能性を論じ、資本コストの10-15%削減などの利点を示す。規制当局への提言として、XBRL-ESGタグ付けの義務化やハイブリッド保証モデルを挙げる。

English

This study examines the impact of blockchain, AI, big data, and XBRL on sustainable financial reporting in emerging markets like Nigeria. Based on stakeholder theory and TAM, it discusses automation of ESG data collection, predictive analytics, and integrated audits, citing benefits like 10-15% reduction in capital costs. Recommendations include mandatory XBRL-ESG tagging and hybrid assurance models.

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

日本ではSSBJ開示が始まり、ESGデータの信頼性確保が課題。本論文の技術活用の議論は、日本の開示実務におけるAI・XBRL活用の参考になる。

In the global GX context

With ISSB and CSRD driving global disclosure, this paper offers insights on how emerging technologies can enhance ESG data quality and assurance, relevant for global standard-setting and fintech innovation.

👥 読者別の含意

🔬研究者:技術とESG報告の統合に関する理論的枠組みと新興市場の事例を提供。

🏢実務担当者:ESGデータ収集・保証プロセスへの技術導入のメリットと課題を理解できる。

🏛政策担当者:規制当局はXBRL-ESGタグ付けやハイブリッド保証モデルの提言を参考にできる。

📄 Abstract(原文)

This research focuses on the revolutionary impact of various modern technologies namely, blockchain, artificial intelligence, big data analytics, and XBRL on the sustainable financial reporting scenario in parts of the world that are just starting to be awakened financially, like Nigeria where there are also global regulations such as the European Union's CSRD and the ISSB frameworks. The research is based on stakeholder theory, legitimacy theory, and the Technology Acceptance Model. Thus it delves into the core of problems that are characteristic of the traditional way of reporting and that include data silos, manual errors, greenwashing risks, and inconsistent ESG disclosures that are causing a lack of transparency and preventing alignment with the SDGs. The research provides a thorough literature review on how the technologies mentioned above can perform different functions such as automating the collection of ESG data, providing immutability through distributed ledgers, creating predictive sustainability analytics, and conducting integrated audits, thus increasing the trust of stakeholders, compliance with regulations, and the obtaining of long-term value. Although there are still interoperability problems, cybersecurity weaknesses, a lack of skilled personnel, and expensive implementations in areas with limited infrastructure, the best practices of world leaders have shown measurable advantages, such as a decrease in capital costs by 10-15% and the availability of real-time dashboards for double materiality assessments. The results emphasize the role of technology in reconciling financial opacity with accountability and providing regulators with actionable recommendations such as obligatory XBRL-ESG tagging, public-private training partnerships, and hybrid assurance models as a priority. From a theoretical perspective, it broadens adoption dynamics; from a practical standpoint, it directs fintechs towards building resilient, transparent reporting ecosystems.

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