The Application of Machine Learning to Sustainable Finance
Erik Allen, Kevin Lyons, Rodrigo Tavares
Published in Journal of Environmental Investing, 2017, Vol. 8, no. 1, p. 115-128
This article explores the various ways machine learning (ML), one of the applications of artificial intelligence, can be applied to sustainable finance. In the first part of the article we describe the crucial role that ML plays in the financial ecosystem, from managing assets to assessing risks. We also highlight the growing relevance of the global environmental, social, and governance (ESG) market. The second part describes how ML, in combination with big data, can present a robust instrument for ESG data to be assessed in an efficient, standardized, and objective fashion. We argue that ML will eventually enable the identification of materially relevant ESG indicators from the large universe of current ESG metrics, automatically identifying variations by industry, geography, and firm size. However, doing so will require additional standardization of reporting. ML has a role to play in the near-term by providing a set of tools to enable real-time monitoring of sustainability performance.
