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JPX Publishes “Survey of TCFD Disclosure Using Generative AI”

JPX

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March 26, 2024 2 min read
JPX Publishes “Survey of TCFD Disclosure Using Generative AI”

Following its “Surveys of TCFD Disclosure in Japan” published in FY2021 and FY2022, Japan Exchange Group, Inc. (JPX) has published a “Survey of TCFD Disclosure Using Generative AI,” covering Tokyo Stock Exchange (TSE) listed companies (2,198 domestic listed companies that submitted Annual Securities Reports between April 1 and October 31, 2023).

 

This fiscal year’s survey utilizes the results of research which looked to use generative AI to automatically determine whether information was disclosed corresponding to each of TCFD’s Recommended Disclosures in the Annual Securities Reports of TSE listed companies (see JPX Working Paper “Automated Determination of TCFD Recommended Disclosures through Zero-shot Text Classification Using Large Language Models”). Given that the amended Cabinet Office Ordinance on Disclosure of Corporate Affairs, etc. (implemented January 31, 2023) applied to Annual Securities Reports covering business years ending on or after March 31, 2023, this research used generative AI to try to automatically determine disclosure rates in Annual Securities Reports submitted on or after April 1. For this reason, the coverage in this year’s survey is much wider than in previous years, and it has become possible to shed light on differences between disclosure rates by market segment, company size, and sector.

 

We hope that this survey can be of help to listed companies preparing their climate-related disclosure, as well as to all parties in their work to enhance the quality and quantity of disclosed information.

Survey of TCFD Disclosure Using Generative AI icon-pdf

Related Links

JPX Working Paper “Automated Determination of TCFD Recommended Disclosures through Zero-shot Text Classification Using Large Language Models” can be accessed through the below links.

“Surveys of TCFD Disclosure in Japan” to date can be found on the below page.

Related links