Creating talking points for client advisers at banks to promote sustainable investing

Ewe Zi Yi, Pradeep Reddy Varakantham and Alan Megargel
Additional contact information
Ewe Zi Yi: Machine Learning Engineer, Gojek, Singapore
Pradeep Reddy Varakantham: School of Computing and Information Systems, Singapore
Alan Megargel: Singapore Management University, Singapore

Journal of AI, Robotics & Workplace Automation, 2025, vol. 3, issue 4, 350-361

Abstract: Environmental, social and governance (ESG) factors have become key non-financial factors for investors to evaluate companies with respect to understanding material risks and growth opportunities. While not mandatory, companies are providing ESG reports that outline progress in different ESG metrics (six broad metrics and 15 specific ones). Client advisers (CAs) read these reports to identify key metrics of interest to investors. Given the number of companies and investment products, however, it is not feasible for CAs to read all the reports, which can sometimes run into tens or hundreds of pages). The authors have developed multiple frameworks building on leading approaches in natural language understanding (NLU) to identify relevant talking points in each document and then filter out the most important ones. A large bank has evaluated these approaches on a proprietary dataset of more than 100 sustainability reports and provided an F1 score of over 0.8. The system is currently being evaluated for integration into the bank’s decision-assist framework for client advisers. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.

Keywords: machine learning; natural language processing; investment products; client advisers; talking points (search for similar items in EconPapers)
JEL-codes: G2 M15 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://hstalks.com/article/9224/download/ (application/pdf)
https://hstalks.com/article/9224/ (text/html)
Requires a paid subscription for full access.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aza:airwa0:y:2025:v:3:i:4:p:350-361

Access Statistics for this article

More articles in Journal of AI, Robotics & Workplace Automation from Henry Stewart Publications
Bibliographic data for series maintained by Henry Stewart Talks ().