{"id":395108,"date":"2020-12-08T07:07:27","date_gmt":"2020-12-08T12:07:27","guid":{"rendered":"http:\/\/www.marketnewsdesk.com\/?p=395108"},"modified":"2020-12-08T07:07:27","modified_gmt":"2020-12-08T12:07:27","slug":"ping-an-uses-artificial-intelligence-to-detect-greenwashing-and-assess-impact-of-climate-risk-disclosure-transparency-on-financial-performance","status":"publish","type":"post","link":"https:\/\/www.marketnewsdesk.com\/index.php\/ping-an-uses-artificial-intelligence-to-detect-greenwashing-and-assess-impact-of-climate-risk-disclosure-transparency-on-financial-performance\/","title":{"rendered":"Ping An Uses Artificial Intelligence to Detect Greenwashing and Assess Impact of Climate Risk Disclosure Transparency on Financial Performance"},"content":{"rendered":"
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AI-driven transparency indicators complement ESG ratings and analytic tools in market<\/h2>\n

PR Newswire<\/p>\n<\/p><\/div>\n

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\n HONG KONG<\/span> and SHANGHAI<\/span>, Sept. 8, 2020<\/span> \/PRNewswire\/ —\u00a0Natural Language Processing (NLP) technology, used to analyze language from company disclosures, can help to detect potential “greenwashing” by high emission companies, according to the latest report from the Ping An Digital Economic Research Center (PADERC), a member of Ping An Insurance (Group) Company of China<\/span>, Ltd. (HKEx:2318; SSE:601318), and the Brevan Howard Centre for Financial Analysis at Imperial College London, the world’s leading climate finance research center.<\/p>\n

The report, “Climate Disclosures and Financial Performance”, also found that artificial intelligence (AI)-based climate disclosure indicators perform better than some existing ESG ratings at differentiating green companies from other high emission companies \u2013 making these tools a valuable complement to ESG ratings for investment analysis.<\/p>\n

The study found that firms with better disclosure of financial impact metrics tend to have higher valuations, lower leverage and lower cost of capital, after controlling for carbon emissions and other firm characteristics. Large cap firms that follow the TCFD recommendations tend to have higher valuations, but small and medium cap firms engaging in climate disclosures may still offer considerable opportunities for appreciation. A range of existing ESG ratings, however, appear to have a weak or inconclusive bearing on valuations.<\/p>\n

“AI-based indicators offer a valuable addition to the asset manager’s toolkit to enhance and refine their investment screening process, with more objective information on the climate risk exposure of firms,” said Chenxi Yu<\/span>, Deputy Director of Ping An Digital Economic Research Center. “They can also detect potential greenwashing that may be at play in particular companies.”<\/p>\n

The researchers developed a series of AI-based indicators related to climate risks and financial impacts, drawing from the guidelines of Task Force on Climate-related Financial Disclosures (TCFD) for relevant words and expressions. The NLP techniques automatically assessed the coverage of the indicators in the climate risk disclosure reports of US and Chinese firms in the S&P 500 and the CSI 300.<\/p>\n

\n Under-reporting of climate metrics by high emission firms may be erroneously rewarded<\/b>\n <\/p>\n

The study found that AI-driven indicators perform better than some traditional ESG ratings to detect corporate “greenwashing” \u2013 providing misleading or incomplete information to give the impression that a company is more environmentally responsible than it actually is. The indicators were better than some ESG ratings in differentiating between so-called “brown” firms \u2013 those in high emission industries, such as mining, transportation, and infrastructure — and lower emission firms.<\/p>\n

The indicators found patterns in the disclosure among brown firms, including:<\/p>\n