An Innovative Knowledge Graph approach to extract high volumes of climate and environmental structured and unstructured data

信息过载是一个普遍的问题，特别是在金融等数据密集型行业。非结构化文本，如公司报告、新闻、成绩单、电子邮件和备忘录，包含许多有价值的信息，但这些信息往往被数据分析师和关键决策者遗漏，例如在评估风险和投资时。为了做出准确的决策并避免“绿色清洗”，金融公司必须依赖的不仅仅是公司对其业务活动可持续性的披露。然而，目前的解决方案并不能在数据集中直观地显示这些链接，从而帮助决策者做出更好、更明智的决策。Auquan将通过开发知识图谱技术来解决这一重要的、未满足的全球需求，该技术可以直观地链接相关但通常隐藏的见解，而不会让用户因大量数据而不知所措。我们的解决方案从非结构化和结构化数据集中提取信息，从而在金融领域做出更好的决策，提高用户的工作效率。这是“绿色金融”的一大步，因为它确保了气候和环境因素带来的金融风险无缝地融入主流金融决策。

Information overload is a common problem, particularly in data heavy industries like finance. Unstructured text, such as company reports, news, transcripts, emails and memos, contain much valuable information that is often missed by data analysts and key decision makers, for example when assessing risk and investments.Access to scientifically robust climate and environmental data and analytics is particularly patchy and unreliable. To make accurate decisions and avoid green-washing, financial firms have to rely on more than just company disclosures about the sustainability of their business activities. However, current solutions do not visually display these links in datasets that could help decision makers make better, more informed decisions.Auquan will solve this significant, unmet, global need by developing knowledge graph technology that visually links relevant, but often hidden, insights without overwhelming the user with high volumes of data. Our solution extracts information from both unstructured and structured datasets, leading to better decisions and more productive users in the finance sector. This is a big step change in 'greening finance', because it ensures that financial risks from climate and environmental factors are seamlessly integrated into mainstream financial decision-making.