The Application of Artificial Intelligence (AI) in the Implementation of ESG-Oriented Sustainable Development Strategies in the Banking Sector: A Case Study
銀行セクターにおけるESG指向の持続可能な発展戦略の実施における人工知能（AI）の適用：事例研究 (AI 翻訳)
Przemysław Pluskota, Kamila Słupińska, Agata Wawrzyniak, Barbara Wąsikowska
🤖 gxceed AI 要約
日本語
本論文は、銀行がデジタル・モバイルバンキングにおいてAIを活用し、ESG戦略（特に環境側面）を実施・伝達する方法を理論的・実証的に分析する。混合手法を用い、欧州の規制枠組みや事例研究から、グリーン投資推奨、カーボンフットプリント分析、自動化されたサステナビリティ報告、倫理的コミュニケーションにおけるAIの有効性を示す。一方で、アルゴリズムの透明性やデータバイアスなどの課題も指摘する。
English
This paper analyzes how banks apply AI in digital/mobile banking to implement and communicate ESG strategies, focusing on environmental dimensions. Using mixed methods including case studies and European regulatory frameworks, it finds AI supports green investment recommendations, carbon footprint analytics, automated sustainability reporting, and ethical client communication. It also highlights challenges like algorithmic transparency and data bias.
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
日本の金融機関でもSSBJ基準対応やTCFD開示が進む中、AIによるESGデータ分析や報告自動化は実務効率化に直結する。本論文は欧州の先行事例を提供し、日本におけるAI活用の可能性と課題を考察する上で参考となる。
In the global GX context
As global frameworks like ISSB and CSRD demand more granular ESG data, AI-driven analytics and reporting tools are becoming critical for banks. This paper provides empirical evidence on how European banks leverage AI for sustainability, offering insights for financial institutions worldwide transitioning to low-carbon operations.
👥 読者別の含意
🔬研究者:Provides a useful taxonomy of AI applications in banking ESG and identifies research gaps for further study.
🏢実務担当者:Highlights practical AI tools for carbon footprinting, green investment, and automated reporting that can be adapted for corporate sustainability teams.
🏛政策担当者:Offers insights into regulatory implications of AI in sustainable finance, informing oversight of algorithmic transparency and data bias.
📄 Abstract（原文）
This paper presents a theoretical and empirical analysis of how banks apply artificial intelligence (AI) in digital and mobile banking to implement and communicate ESG (Environmental, Social, and Governance) strategies, with particular emphasis on environmental dimensions of sustainable finance. The study adopts a mixed methodological approach combining desk research, encompassing a synthesis of academic studies, industry reports, and European regulatory frameworks on AI and ESG, and case study analysis of selected banks implementing AI-based sustainability solutions. The findings reveal that AI supports ESG strategy implementation primarily through green investment recommendations, carbon footprint analytics, automated sustainability reporting, and ethical communication with clients. AI-driven tools enhance the operational efficiency, transparency, and customer engagement of financial institutions while simultaneously fostering low-carbon financial behaviors. However, the study also highlights ethical and governance challenges related to algorithmic transparency, data bias, and responsible AI oversight. The paper contributes to the growing body of literature on AI-driven digital transformation and sustainable finance by identifying research gaps and outlining future directions for exploring the role of AI in accelerating the transition of the banking sector.
🔗 Provenance — このレコードを発見したソース
- openaire https://doi.org/10.3390/su18020732first seen 2026-05-14 21:39:54
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