Ping An Group, a Chinese financial services conglomerate that incorporates China’s second-largest life insurer, is seeking to combine artificial intelligence (AI) with environmental, social and governance (ESG) information to drive its investing decisions.
The organisation believes combining the two will enable it to make rapid and astute investment decisions based on ESG data.
“We have been working on something meaningful in the past two years, known as AI-ESG… We have not heard anyone using this means to do ESG management [among our peers], so if our policy tool set becomes matured in the future, we can empower the industry with this set of tools,” Richard Sheng, board secretary and brand director of Ping An, told AsianInvestor in an interview.
Ping An’s AI-ESG essentially consists of two elements: an integrated management platform and an intelligent investment platform. The former one, launched last year, collects and sorts out ESG data to form a knowledge base – effectively a store of large amounts of processed data and information.
The group is currently building the latter investment platform and intends to complete it in the third quarter this year. It will be designed to offer Ping An analysts ESG-related investment suggestions, depending on their specific needs.
At present, Ping An Group has about Rmb1 trillion ($143 billion) in total in responsible investments. The number includes the financial products of the group as a product issuer, a company spokesman said.
ADDING ESG LABELS
By way of example, Sheng said one scenario where Ping An's AI-ESG capabilities will prove useful is in the coal industry. It is obviously carbon emission-heavy and a sector where Ping An has internal investment restrictions but not a blanket investment ban.
When a new coal-linked investment or investment project is entered into the system, the AI-ESG system is designed to automatically generate a new label that will match up relevant policy papers. In addition, when the ESG investment platform is complete new labels will be added to give appropriate investment guidance to the analyst who inquires, said Sheng.
This sort of data-focused sorting is increasingly required, given that ESG involves a lot of policy papers and principles. Sheng said that about 500 labels have so far been placed in the system. Manually incorporating all these labels in the investment process would be inefficient and error-prone, whereas properly constituted AI-ESG programmes can automatically match these labels with the relevant investment projects.
Another feature of the system will be its ability to help to trace how mistakes are made in investment decisions from an ESG perspective. It can help to identify when and how deviations from ESG principles have happened in the investment process, thus strengthening performance management of ESG, he added.
Ping An has increasingly been leading the way in China’s ESG drive. The financial group is the first China asset owner to have signed Climate Action 100+ and the United Nations’ Principle of Responsible Investment (UN PRI), in December and September last year, respectively. Climate Action 100+ is an investor initiative to help reduce greenhouse gas emissions, while UN PRI signatories are to incorporate ESG factors into their investment and ownership decisions.
Ping An’s external managers are also obliged to comply with greenhouse gas emission rules after it signed Climate Action 100+, forming part of its efforts to lift ESG standards in China. While the country remains the world’s largest carbon emitter, Beijing’s encouragement of green finance has helped ESG investing to gradually gain momentum in the country.
Ping An’s desire to mix ESG and AI make sense. A report by S&P Global highlighted that AI allows investors to process mountains of data that holds essential information for ESG analysis. That means they can collect and analyse more information than ever.
Computer algorithms that have been trained can digest all of the information available about a company at a reasonable speed, whereas it would be a massive undertaking for a human being, the report added.
The success of AI to make a difference ultimately depends a lot on the availability of reliable data. “As investors, one of our key challenges is how to translate the ESG information gathered into actionable investment insights. As such, ESG data availability, quality and comparability is critical,” Paul Milon, ESG specialist for Asia Pacific at BNP Paribas Asset Management, told AsianInvestor.
The good news for Ping An’s plans is that recent regulatory efforts to encourage greater disclosure of ESG data is working in its favour.
The China Security Regulatory Commission has ordered that listed Chinese companies mandatorily disclose environmental information from 2020. This should help to enhance data availability and comparability, Milon said.
The availability of ESG data is also developing rapidly after the greater inclusion of China A-shares in international indices, as it has prompted more ESG data providers and international investors to ask Chinese companies about ESG, he added.