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Audit 4.0-based ESG assurance: An example of using satellite images on GHG emissions

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  • Gu, Yu
  • Dai, Jun
  • Vasarhelyi, Miklos A.

Abstract

As Environment, Social, and Governance (ESG) information has become an essential resource for investors, regulators have attempted to assure its quality. While more companies offer ESG disclosure, it is usually not fully substantiated with supporting information. Assurance is needed to verify that ESG reports are free of substantive errors. However, traditional financial audit approaches are less effective in providing ESG assurance due to the difference in the nature of evidence, difficulty in measuring and verifying ESG measures, and ever-changing ESG performance. To increase the effectiveness of ESG audit approaches, this study proposes Audit 4.0-based ESG assurance, which uses Big Data and emerging technologies of Audit 4.0 to capture evidence from the physical world and provide accurate assurance on ESG reports in a timely manner. We further perform a case study as a proof of concept of the proposed approach, which explores the integration of satellite-based methane estimation as ESG audit evidence. The use of satellite images provides opportunities for regulators and companies to monitor and assure ESG reports in a continuous manner.

Suggested Citation

  • Gu, Yu & Dai, Jun & Vasarhelyi, Miklos A., 2023. "Audit 4.0-based ESG assurance: An example of using satellite images on GHG emissions," International Journal of Accounting Information Systems, Elsevier, vol. 50(C).
    • Handle: RePEc:eee:ijoais:v:50:y:2023:i:c:s1467089523000179
    DOI: 10.1016/j.accinf.2023.100625
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    2. He, Ling-Yun & Wang, Liang, 2025. "Can artificial intelligence curb greenwashing? Firm-level evidence based on large language model," Energy Economics, Elsevier, vol. 152(C).

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