公司年报中气候风险披露的自动识别
Automated Identification of Climate Risk Disclosures in Annual Corporate Reports
摘要：
决策者必须了解哪些金融政策能够有效地增加公司报告中的气候风险披露。我们使用机器学习自动识别五种不同类型的气候相关风险的披露。为此，我们创建了一个数据集，其中包含欧洲公司的120多份手动注释的年度报告。应用我们的方法报告的337家公司在过去的20年中，我们发现，风险披露正在增加。过渡风险的披露比实体风险的披露更具动态性，而且各行业之间存在显著差异。具体国家的动态表明，监管环境可能在增加披露方面发挥重要作用。
英文摘要：
It is important for policymakers to understand which financial policies are effective in increasing climate risk disclosure in corporate reporting. We use machine learning to automatically identify disclosures of five different types of climate-related risks. For this purpose, we have created a dataset of over 120 manually-annotated annual reports by European firms. Applying our approach to reporting of 337 firms over the last 20 years, we find that risk disclosure is increasing. Disclosure of transition risks grows more dynamically than physical risks, and there are marked differences across industries. Country-specific dynamics indicate that regulatory environments potentially have an important role to play for increasing disclosure.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
