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Evaluating the Anti-Corruption Factor in Environmental, Social, and Governance Indices by Sampling Large Financial Asset Management Firms

Author

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  • Kenneth David Strang

    (Business Analytics Department, W3-Research, St. Thomas, VI 00802, USA
    Plaster Graduate School of Business, University of the Cumberlands, Williamsburg, KY 40769, USA
    Business School, RMIT University, Melbourne, VIC 3004, Australia)

  • Narasimha Rao Vajjhala

    (Faculty of Engineering and Architecture, University of New York Tirana, 1048 Tirana, Albania)

Abstract

Current Environmental, Social, and Governance (ESG) indices are flawed because the data are incomplete and not reported consistently, and some measured factors may be irrelevant to the industry. Regulators in the financial services industry emphasize reporting CO 2 emissions (environmental factor), yet the key resources leveraged for production are rented offices, and internet–governance issues like money laundering, corruption, and unethical behavior would be more relevant. To investigate this problem, we sampled the finance and insurance industry firms in the USA with the greatest economic impact, i.e., those managing at least USD 1 trillion in assets. We used artificial intelligence to collect data about undisclosed legal decisions against firms to measure the ESG anti-corruption governance factor GRI 206-1, defined by the Global Reporting Institute (GRI) for global sustainable development goals (SDGs), which correspond to the United Nations’ SDGs. We applied Bayesian correlation with bootstrapping to test our hypotheses, followed by root cause analysis. We found that ESG ratings from providers did not reflect legal cases decided against firms; the Bayesian BF +0 odds ratio was 3005 (99% confidence intervals were 0.617, 0.965). Also, misconduct fines and arbitration legal case counts were significantly related for the same firm (the Vovk-Selke maximum p-ratio was 4411), but most ESG scores were significantly different for the same firm. We found three other studies in the literature that corroborated some of our findings that specific firms in our sample were considered to be unethical. We propose deeper study of the implications related to our findings based on public interest and stakeholder theory.

Suggested Citation

  • Kenneth David Strang & Narasimha Rao Vajjhala, 2024. "Evaluating the Anti-Corruption Factor in Environmental, Social, and Governance Indices by Sampling Large Financial Asset Management Firms," Sustainability, MDPI, vol. 16(23), pages 1-27, November.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:23:p:10240-:d:1527369
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    References listed on IDEAS

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