INNOV Phase I: Leverage artificial intelligence to improve Environmental, Social, and Governance (ESG) data

负责任投资原则（PRI）由联合国环境规划署金融倡议于2005年建立，旨在为改善投资过程中的环境、社会和治理问题（ESG）分析提供框架，并帮助公司在管理其投资时采取负责任的做法。资产管理公司和其他金融机构越来越依赖ESG评级机构来评估、衡量和比较公司的ESG绩效。在风险/回报策略中整合ESG影响有助于那些愿意通过投资于可持续市场来赚取利润的投资者。然而，目前还没有明确的方法标准来衡量ESG绩效，也没有将ESG信息整合到经典的风险/回报组合优化框架中。然而，这些标准的出现将有很大的潜力鼓励投资者在决策中系统地采用ESG信息。反过来，这也将激励公司通过向更可持续的活动发展来赚取商业价值。我们建议通过使用最先进的自然语言处理（NLP）方法，从公司的报告、新闻和社交媒体帖子中自动提取相关的ESG信息，来研究框架的发展。我们不提供ESG分数，而是提供ESG数据，以提高透明度和可比性，并帮助投资者做出更明智的决策。我们的客户将受益于一个网络界面，他们可以在其中搜索公司并检索其ESG信息。该项目的成果为可持续金融市场带来了极好的机遇。蒙特利尔正在成为人工智能和可持续金融的中心。我们相信，我们的产品能够帮助魁北克成为人工智能和可持续金融这两个行业的领导者。通过更好地告知投资者，我们希望我们的技术能引导更多的资金流向那些实践和价值观符合加拿大环境、社会和治理准则的公司。

The Principles for Responsible Investment (PRI) were established in 2005 by the Financial Initiative of the United Nations Environment Program with the objective of providing a framework for improving the analysis of environmental, social, and governance issues (ESG) in the investment process and to help companies exercise responsible practices in managing their investments. Asset managers and other financial institutions are increasingly relying on ESG rating agencies to assess, measure, and compare the ESG performance of companies. Integration of the ESG impact within risk/return strategies helps investors who are willing to earn profit by investing in a sustainable market. However, no clear methodological standard has yet emerged, neither for measuring ESG performance nor for integrating ESG information into classical risk/return portfolio optimization frameworks. Yet, the emergence of such standards would have a great potential to encourage investors to adopt ESG information systematically in their decisions. In return, this would also incentivize companies to earn business value by evolving toward more sustainable activities.We propose to investigate the development of a framework by automatically extracting relevant ESG information from companies' reports, news, and social media posts using state-of-the-art Natural Language Processing (NLP) methods. Instead of offering ESG scores, we provide ESG data that promotes transparency and comparability and helps investors to make better-informed decisions. Our clients will benefit from a web interface in which they can search for a company and retrieve its ESG information. The outcome of this project brings an excellent opportunity to the sustainable finance market. Montreal is becoming a center of AI and sustainable finance. We believe our products specifically help Quebec to be a leader in both industries, AI and sustainable finance. By better informing the investors, we hope our technology directs more capital toward companies whose practices and values align with environmental, social, and governance precepts in Canada.