Leveraging Computational Intelligence for SDG-KPI Mapping and ESG Data Integration: A Technology-Driven Framework for Sustainable Accounting Disclosure

WanYunhan

doi:10.54254/2755-2721/2025.24511

Applied and Computational EngineeringOpen access

Leveraging Computational Intelligence for SDG-KPI Mapping and ESG Data Integration: A Technology-Driven Framework for Sustainable Accounting Disclosure

Research Article

Open Access

Leveraging Computational Intelligence for SDG-KPI Mapping and ESG Data Integration: A Technology-Driven Framework for Sustainable Accounting Disclosure

WanYunhan ^1*

¹ University of Auckland, Auckland, New Zealand

^*Corresponding author: rara481846778@gmail.com

Published on 4 July 2025

ACE Vol.176

ISSN (Print): 2755-273X

ISSN (Online): 2755-2721

ISBN (Print): 978-1-80590-239-3

ISBN (Online): 978-1-80590-240-9

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Abstract

In corporate sustainable development practice, how to accurately align independently disclosed key performance indicators (KPIs) with the United Nations Sustainable Development Goals (SDGs) has long faced challenges such as ambiguous standards and complex operations. This research develops an intelligent analysis model. By integrating natural language processing and knowledge graph technology, it automatically maps ESG disclosure data and SDGs. The semantic analysis system, built from 200 cross-industry ESG reports, applies a text vectorization algorithm and dynamic weight adjustment mechanism, achieving a matching accuracy of 91% in identifying environmental governance indicators and a coverage rate of 86% in social indicators. The model innovatively introduces the GRI standard knowledge graph, effectively solving the problem of differences in information disclosure standards across industries. This system provides audit institutions with automated verification tools, assists regulators in establishing dynamic monitoring mechanisms, and promotes the transformation of companies' ESG practices from formal compliance to substantive innovation. The research results have practical value in breaking the current fragmented situation of information disclosure for sustainable development and provide technical support for building a reliable global accountability governance system.

Keywords:

Computational Intelligence, SDG-KPI Mapping, ESG Reporting, Ontology Matching, Sustainability Disclosure

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References

[1]. Nielsen, C. (2023). ESG reporting and metrics: From double materiality to key performance indicators. Sustainability, 15(24), 16844. https://doi.org/10.3390/su152416844

[2]. Erin, O. A., Bamigboye, O. A., & Oyewo, B. (2022). Sustainable development goals (SDG) reporting: An analysis of disclosure. Journal of Accounting in Emerging Economies, 12(1), 1–23. https://doi.org/10.1108/JAEE-12-2021-03082

[3]. Molnár, P., Suta, A., Lukács, B., & Tóth, Á. (2024). Linking sustainability reporting and energy use through global reporting initiative standards and sustainable development goals. Clean Technologies and Environmental Policy. https://doi.org/10.1007/s10098-024-03044-1

[4]. Bronzini, M., et al. (2023). Glitter or gold? Deriving structured insights from sustainability reports using large language models. arXiv preprint arXiv:2310.05628. https://arxiv.org/pdf/2310.05628

[5]. Sachs, J., Kroll, C., Lafortune, G., Fuller, G., & Woelm, F. (2021). The decade of action for the sustainable development goals: Sustainable development report 2021. Cambridge University Press. https://sdgtransformationcenter.org/reports/sustainable-development-report-2021sdgtransformationcenter.org

[6]. Bamigboye, O. A., Erin, O. A., & Oyewo, B. (2022). Sustainable development goals (SDG) reporting: An analysis of disclosure. Journal of Accounting in Emerging Economies, 12(1), 1–23. https://doi.org/10.1108/JAEE-12-2021-03082

[7]. Essig, T., & Thoma, M. (2021). Leveraging the SDGs and deep learning to evaluate companies' sustainability efforts. Master's thesis, Copenhagen Business School. https://research.cbs.dk/files/68333871/1113575_Master_Thesis_Essig_Thoma_20210516.pdfresearch.cbs.dk

[8]. Kumar, R., & Sharma, A. (2023). Composite or component-wise ESG reporting: A tangle. Vision: The Journal of Business Perspective. https://doi.org/10.1177/09726225241264618

[9]. Molnár, P., Suta, A., Lukács, B., & Tóth, Á. (2024). Linking sustainability reporting and energy use through global reporting initiative standards and sustainable development goals. Clean Technologies and Environmental Policy. https://doi.org/10.1007/s10098-024-03044-1

[10]. Bronzini, M., et al. (2023). Glitter or gold? Deriving structured insights from sustainability reports using large language models. arXiv preprint arXiv:2310.05628. https://arxiv.org/pdf/2310.05628

References

[1]. Nielsen, C. (2023). ESG reporting and metrics: From double materiality to key performance indicators. Sustainability, 15(24), 16844. https://doi.org/10.3390/su152416844

[8]. Kumar, R., & Sharma, A. (2023). Composite or component-wise ESG reporting: A tangle. Vision: The Journal of Business Perspective. https://doi.org/10.1177/09726225241264618

Cite this article

WanYunhan, (2025). Leveraging Computational Intelligence for SDG-KPI Mapping and ESG Data Integration: A Technology-Driven Framework for Sustainable Accounting Disclosure. Applied and Computational Engineering,176,1-7.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of the 3rd International Conference on Machine Learning and Automation

ISBN: 978-1-80590-239-3(Print) / 978-1-80590-240-9(Online)

Editor: Hisham AbouGrad

Conference website: 978-1-80590-240-9

Conference date: 17 November 2025

Series: Applied and Computational Engineering

Volume number: Vol.176

ISSN: 2755-2721(Print) / 2755-273X(Online)

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