Financial Services

Green intelligence: Asia’s ESG investing, data integrity and technology

December 09, 2019


December 09, 2019

Jason Wincuinas

Manager, Policy and insights

Based in Hong Kong, Jason covers Asia from Australia to India. His background includes managing publications, financial reporting and technical marketing as well as a decade of product-sourcing experience with mainland China factories. Some of his most formative work, however, has been as a stay-at-home dad and freelance writer, covering topics from perfluorocarbons to popcorn. Jason received a BA in English from the University of Massachusetts, Amherst with study at the University of Sheffield in Yorkshire, UK.

Environmental, social and governance (ESG) investing has evolved from the rather straightforward approach of stock exclusion to more sophisticated and data-heavy frameworks. How investment firms are tackling this ESG data load is a key question. This research analyses the degree to which artificial intelligence (AI) is being deployed, how it is being used and what more it might do in the future for ESG investment decisions. Integral to that question is an investigation into the state, availability and integrity of ESG data in Asia. Big data has offered insight in many other business sectors and industries, but is Asia’s ESG data big enough yet to be meaningful?

The Economist Intelligence Unit surveyed decision-makers at a spectrum of large asset owners and institutional investors about their observations related to “impact” versus “income” goals and about sentiment on data quality. We also spoke to a range of experts on the same topics to study how AI technology may be changing the investment world, specifically with regard to improving ESG returns or impact.

The key findings are as follow:

  1. The rise of ESG in Asia: some 95% of respondents believe that ESG investing is important to their firm, with the overwhelming majority saying it will be more so in three years. More than 80% believe ESG has a positive impact on returns.
  2. ESG factor weighting: almost half of respondents said they weighted environmental, social and governance factors equally. For the remainder that didn’t, the individual most important factor was environmental, with mainland China’s increasing focus on such issues a major driver. About 90% of respondents feel that environmental and social issues will gain the same importance as governance within a decade.

  3. Investors’ AI uptake: pension funds have the highest uptake of AI for ESG screening. There is, however, broad usage across all investor types and regions. A rapidly expanding range of AI techniques, drawing information from diverse sources, is being used to fill gaps in standard corporate disclosures.

  4. Data quality and suitability: while there is broad satisfaction with available data, this is combined with recognition that gaps exist. Most investors are responding to such limitations by conducting their own research on the information available.

  5. Looking forward: much ESG-related data are backwards-facing and cannot, therefore, identify ongoing change in corporate behaviour. The promise of adding AI to the equation is to get a more forward view. Analytics companies are developing models to flag behavioural shifts and experts stress that focusing on data only misses the importance of how it is framed—something that remains a very human decision.

Enjoy in-depth insights and expert analysis - subscribe to our Perspectives newsletter, delivered every week