A Professor Who Never Stops Asking Questions Turning an ESG Challenge into AI Research, Winning an International Award
From the challenge of evaluating ESG data—a process that demands both time and expertise—came the development of AI research that helps analyze data systematically and transparently, with real-world applications in the Thai capital market.
As ESG data becomes an increasingly important factor in investors’ decision-making, the process of gathering and evaluating information from a large volume of reports still requires significant time and specialized expertise. A simple question—can AI make this process faster, more transparent, and more explainable?—became the starting point for the research that led Dr. Parisa Jindaluang, a faculty member of the School of Accounting at Bangkok University, to win the Runner-up Award from the Capital Market Research Award in Equity Market program.
From a Capital Market Challenge to the Start of a Research Project
Behind this research lies Dr. Parisa’s interest in ESG, sustainability reporting, capital markets, and the application of AI to accounting and finance. She observed that the ESG data of most listed companies exists in text form and is scattered across various types of reports, making the process of gathering and evaluating this data both time-consuming and heavily reliant on expert judgment. This gave rise to the idea of using AI to help read, analyze, and evaluate the data in a systematic way—reducing workload while meeting the needs of the Thai capital market.
AI-Driven ESG Disclosure Scoring: Research That Extends to Real-World Application
Dr. Parisa explains that the research, titled “AI-Driven ESG Disclosure Scoring for Thai Listed Firms,” studied data from 541 companies listed on the Stock Exchange of Thailand between 2022 and 2024. The study used Large Language Models (LLMs) to extract ESG information from text, Machine Learning to predict disclosure scores, and Explainable AI to clarify the factors influencing those scores—together forming a systematic and verifiable approach to ESG evaluation. The findings showed that the model could explain ESG disclosure scores at a high level, achieving an R² value of 0.82 and outperforming traditional analytical methods. The research can also be extended into a dashboard that would allow investors, regulators, and listed companies to put the data to practical use.
What Sets This Research Apart
The strength of this work lies in its integration of knowledge across accounting, capital markets, ESG, and AI, combined with the use of real data from 541 Thai listed companies—allowing the findings to comprehensively reflect the context of the Thai capital market. At the same time, the model developed does more than assign scores; it also explains which factors influence the evaluation results, helping to make the application of AI in capital markets more transparent and verifiable. This was another key factor that helped the work earn recognition and win the award.
Beyond the Award: Building on a Body of Knowledge
For Dr. Parisa, the Runner-up Award serves both as encouragement and as confirmation that research can create real value for both academia and the capital market. At the same time, conducting this research allows her to bring real-world knowledge and experience back to her students, showing them that what is learned in the classroom can be extended into solving problems and creating benefits for the business sector. She also credits this success to the support of Bangkok University and the School of Accounting, through policy support, encouragement of research, participation in academic forums, and continuous opportunities for interdisciplinary integration of knowledge.
Good Research Begins with Seeing a Real Problem
Dr. Parisa offers advice to new researchers: research should begin with identifying a real, existing problem, rather than starting from a predetermined choice of statistical method or technology. She encourages an open mind toward learning new fields and a willingness to embrace mistakes, since research must constantly go through trial and development. Importantly, good research does not need to be the most complex—it should be work that answers important questions and creates genuine benefit for real users. She hopes this research will represent another step forward in using AI to elevate the quality of ESG data in the Thai capital market, making the data more transparent, comparable, and more effectively usable in decision-making.