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The preprint article, 𝘿𝙤 𝘽𝙖𝙣𝙠𝙨 𝙎𝙥𝙚𝙖𝙠 𝙩𝙝𝙚 𝙎𝙖𝙢𝙚 𝙀𝙎𝙂 𝙇𝙖𝙣𝙜𝙪𝙖𝙜𝙚? 𝘼 𝙏𝙚𝙭𝙩-𝘽𝙖𝙨𝙚𝙙 𝘾𝙡𝙪𝙨𝙩𝙚𝙧𝙞𝙣𝙜 𝘼𝙥𝙥𝙧𝙤𝙖𝙘𝙝 explores the 𝗻𝗮𝗿𝗿𝗮𝘁𝗶𝘃𝗲 𝗰𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝗰𝘆 in ESG disclosures among leading Italian banks. The authors, Giuseppe Scandurra and Antonio Thomas, employed 𝗰𝗼𝘀𝗶𝗻𝗲 𝘀𝗶𝗺𝗶𝗹𝗮𝗿𝗶𝘁𝘆 and 𝗵𝗶𝗲𝗿𝗮𝗿𝗰𝗵𝗶𝗰𝗮𝗹 𝗰𝗹𝘂𝘀𝘁𝗲𝗿𝗶𝗻𝗴 to analyze the textual content of non-financial reports. Their research identifies 𝗳𝗼𝘂𝗿 𝗱𝗶𝘀𝘁𝗶𝗻𝗰𝘁 𝗿𝗲𝗽𝗼𝗿𝘁𝗶𝗻𝗴 𝗽𝗮𝘁𝘁𝗲𝗿𝗻𝘀 among the banks: 𝘀𝘁𝗮𝗻𝗱𝗮𝗿𝗱𝗶𝘇𝗲𝗱, 𝘁𝗿𝗮𝗻𝘀𝗶𝘁𝗶𝗼𝗻𝗮𝗹, 𝗶𝗻𝘀𝘁𝗿𝘂𝗺𝗲𝗻𝘁𝗮𝗹, and 𝗶𝗱𝗶𝗼𝘀𝘆𝗻𝗰𝗿𝗮𝘁𝗶𝗰. This 𝗿𝗲𝘃𝗲𝗮𝗹𝘀 𝗮 𝗽𝗲𝗿𝘀𝗶𝘀𝘁𝗲𝗻𝘁 𝗱𝗶𝘃𝗲𝗿𝘀𝗶𝘁𝘆 in how banks communicate their ESG efforts, despite calls for harmonization. Ultimately, the study highlights the 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 𝗶𝗻 𝗰𝗼𝗺𝗽𝗮𝗿𝗶𝗻𝗴 𝗮𝗻𝗱 𝗮𝘀𝘀𝗲𝘀𝘀𝗶𝗻𝗴 𝗘𝗦𝗚 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 due to varied reporting styles and suggests a need for more specific standards within the banking sector.

The paper examines how managers strategically adjust the tone of soft information in ESG reports to maximize compensation. It highlights the trade-offs between exaggeration, internal controls, and future reputational costs. Strong incentives with weak controls lead to extreme biases, impacting regulatory decisions, corporate governance, and investor evaluations of ESG disclosures.

The European Commission’s new proposals aim to simplify EU rules, reduce administrative burdens by 25% (35% for SMEs), and boost competitiveness. Targeting sustainable finance, due diligence, and carbon mechanisms, they could save €6.3 billion annually and unlock €50 billion in investments, fostering growth while supporting climate goals.

The EBA report found ESG data is improving but still incomplete. Upcoming regulations like CSRD and ESRS, plus greater transparency in ESG ratings, are expected to significantly enhance data availability and accessibility.

This study explores the use of #ai #foundationmodels, specifically #chatgpt, in #auditing #esgreporting for #compliance with the #eu #taxonomy.