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年制定，旨在提供一个框架，以改善对投资过程中的环境、社会和治理问题（ESG）的分析，并帮助公司在管理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表现。将环境、社会及管治影响纳入风险╱回报策略，有助有意透过投资于可持续发展市场赚取利润的投资者。然而，目前还没有出现明确的方法标准，既没有衡量ESG绩效，也没有将ESG信息纳入经典的风险/回报组合优化框架。然而，这些标准的出现将有很大的潜力鼓励投资者在其决策中系统地采用ESG信息。同时，这也将激励企业通过发展更可持续的活动来获取商业价值。我们建议研究开发一个框架，通过最先进的自然语言处理（NLP）方法，从企业的报告、新闻和社交媒体帖子中自动提取相关的ESG信息。我们不提供ESG评分，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一个极好的机会。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，我们的产品特别有助于魁北克成为人工智能和可持续金融这两个行业的领导者。通过更好地向投资者提供信息，我们希望我们的技术能够将更多的资本引导到那些实践和价值观与加拿大的环境，社会和治理规则相一致的公司。

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.