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It used to be that environmental, social and governance investing meant negatively screening of so-called sin stocks. This is no longer the case, but ESG is still struggling to gain a firm foothold in quantitative investments.
Enter big data and artificial intelligence. According to the July edition of the Cerulli Edge, AI is enabling investors to access huge amounts of information from objective sources, bringing greater frequency, granularity and real-time analysis to ESG investments.
"The use of big data and AI is radically transforming data gathering," Justina Deveikyte, associate director of European institutional research at Cerulli, said in a statement. "These changes have opened up ESG investments to quant funds, which are busy developing new algorithms to systematically evaluate companies."
A recent report found that wealthy younger Americans are intent on leaving legacy influenced by socially responsible spending and investing.
Up to now, ESG has been unable to fully capitalize on quantitative investments, mainly because weaknesses in the data have made it difficult to build strategies, according to Cerulli.
Unlike financial reporting, no universal guidelines exist to steer or compel corporate ESG reporting. Piecemeal information and incomplete data are the norm.
Deveikyte noted that data limitations have affected quant investments in several ways. Big companies, for example, are better at disclosure than small ones. Because most ESG models penalize nondisclosure, this can result in a large-cap bias in portfolios.
But research shows this is changing. A survey of 461 asset managers around the world with approximately $5.4 trillion in assets under management found that while 55% considered lack of robust data a barrier to adoption of ESG today, only 15% said that would be true two years from now.
