Using AI to achieve environmental, social and governance goals

Algorithms can easily crawl and scrape unstructured company data from a range of sources, parsing and converting it into usable structured data, write Terence Tse, Danny Goh and Mark Esposito

Environmental, social and governance (ESG) investments have fast become an important area of interest. It was estimated that sustainable investments amounted to some $30 trillion in 2018, up by 34 per cent from 2016. Indeed, investors (and our societies in general) are increasingly keen to understand whether and by what means businesses are being environmentally and socially responsible and governed. Simultaneously, boards and managements have become cognisant that ESG is crucial to the long-term survival of their companies. Small wonder, then, that some 90 per cent of investors globally already have in place, or have plans to develop, specific ESG investment policies. To guide the selection of such investments, a number of ESG-based rating and index services including MSCI, Bloomberg and Sustainalytics have proliferated in recent years.

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