使用人工智能实证评估企业适应和弹性披露
Roberto Spacey Martín1,2, Nicola Ranger1, Tobias Schimanski3
1London School of Economics and Political Science, London, UK.
概括
可持续性报告中的企业适应和弹性 (A&R) 信息是不够的. 公司需要更多地披露气候风险,指标和目标,以获得更好的财务和监管见解.
科学领域:
- 环境科学 环境科学
- 企业的可持续性 企业的可持续发展
- 适应气候变化 适应气候变化
背景情况:
- 对金融机构,监管机构和政府来说,评估企业对环境变化的适应性和弹性 (A&R) 是至关重要的.
- 虽然可以模拟物理气候风险暴露,但评估企业的脆弱性,适应策略和与社会A&R目标的协调需要更多的数据.
研究的目的:
- 实证评估当前企业可持续性报告中存在的A&R相关信息的程度.
- 发现企业披露的关于适应环境变化和应对环境变化的漏洞.
主要方法:
- 根据既定的可持续发展报告准则,开发了一个新的A&R披露框架.
- 利用先进的大型语言模型 (LLM) 来分析标普500公司的可持续发展报告.
- 结合框架与LLM能力用于经验评估的A&R信息.
主要成果:
- 企业在可持续发展报告中的A&R信息显著缺乏.
- 披露特别缺乏与气候相关的风险,适应指标和特定的A&R目标.
- 目前的报告并没有全面了解公司层面的适应性和弹性.
结论:
- 可持续性报告目前对企业对环境变化的适应性和弹性提供了不充分的信息.
- 为了进行彻底的风险评估,有必要将可持续性报告以外的其他数据源纳入其中.
- 加强企业对A&R的披露对于利益相关者做出明智决策以及实现更广泛的社会弹性目标至关重要.
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