Open-access journal article · 2024
Evaluating the Anti-Corruption Factor in Environmental, Social, and Governance Indices by Sampling Large Financial Asset Management Firms
Sustainability, 16(23), Article 10240 · Published
Summary
What question does this paper answer?
Do the ESG ratings of the world’s largest asset management firms reflect their anti-corruption record — the misconduct and arbitration legal cases they face — and do ESG rating providers agree with each other?
What did the study find?
No. For 14 asset managers each holding more than USD 1 trillion, none of the ESG scores from MSCI, Sustainalytics, or CSRhub was significantly correlated with the firms’ misconduct or arbitration case counts, and the providers disagreed with each other (MSCI vs Sustainalytics r = −0.069). The two legal measures, by contrast, were strongly related (r = +0.897, p < 0.001; Bayesian BF+0 = 3005).
Why does it matter?
Regulators ask financial firms to report CO₂ emissions, yet for firms that mainly rent offices, governance issues such as money laundering and corruption are far more material. The study shows that ESG indices can miss the governance risks that matter most in finance, which matters for investors, regulators, and anyone relying on ESG scores as a proxy for ethical conduct.
This study is part of the evidence overview Can ESG compliance be measured reliably? Evidence from ESG ratings, project-level instruments, machine learning and supply chain records
Key findings
- The study sampled 14 asset management firms with USD 1 trillion to USD 10.8 trillion in assets under management and used AI to collect undisclosed legal decisions as a measure of anti-corruption governance (GRI 206-1).
- None of the ESG scores from MSCI, Sustainalytics, or CSRhub was significantly correlated with the firms’ misconduct or arbitration legal case counts; the Bayes factors for these pairs were all below 1.
- ESG rating providers disagreed: MSCI and Sustainalytics scores for the same firms were uncorrelated (r = −0.069), while MSCI and CSRhub scores agreed (r = +0.891, p < 0.001).
- Misconduct and arbitration case counts were strongly correlated for the same firms (r = +0.897, p < 0.001; Vovk-Sellke maximum p-ratio 4411; bootstrapped Bayesian BF+0 = 3005, 99% CI 0.617–0.965).
- Three corroborating studies identified specific firms in the sample as unethical.
- For finance and insurance firms, governance issues such as money laundering are more material than the CO₂ emissions reporting that regulators emphasize.
Source: Strang & Vajjhala (2024), Sustainability, 16(23), Article 10240. DOI: 10.3390/su162310240
Study at a glance
| Research question | Do ESG ratings capture the anti-corruption governance factor (GRI 206-1) for large financial firms? |
|---|---|
| Sample | 14 asset management firms with USD 1–10.8 trillion in assets under management |
| Data | AI-collected, previously undisclosed legal decisions; misconduct fines; arbitration cases; ESG ratings |
| Methods | Bayesian correlation with bootstrapping |
| Main result | No ESG score correlated significantly with misconduct or arbitration counts; misconduct and arbitration correlated at r = +0.897 (BF+0 = 3005, 99% CI 0.617–0.965; VS-MPR 4411); MSCI and Sustainalytics scores diverged (r = −0.069) |
| Implication | ESG indices under-weight material governance risk in financial services |
| Citation | Strang & Vajjhala (2024) · DOI 10.3390/su162310240 |
Abstract
Current ESG indices suffer from incomplete and inconsistent data, with some factors irrelevant to specific industries. Regulators emphasize CO2 emissions reporting for finance/insurance firms, yet rented offices and governance issues like money laundering prove more material. This study examined USD 1+ trillion asset management firms using AI to collect undisclosed legal decisions measuring anti-corruption governance (GRI 206-1). Bayesian correlation with bootstrapping revealed ESG ratings failed reflecting legal cases (BF+0 odds ratio: 3005, 99% CI: 0.617–0.965). Misconduct fines correlated significantly with arbitration cases (Vovk-Selke p-ratio: 4411), yet most ESG scores diverged for identical firms. Three corroborating studies identified specific sample firms as unethical. The authors recommend deeper investigation of implications regarding public interest and stakeholder theory.
Abstract as published in Sustainability under a Creative Commons licence.
Key terms
- GRI 206-1
- The Global Reporting Initiative disclosure on legal actions for anti-competitive behavior, anti-trust, and monopoly practices — used here as an anti-corruption governance indicator.
- ESG rating divergence
- When different rating agencies give the same company substantially different ESG scores.
- Bayes factor (BF)
- The ratio of evidence for one hypothesis over another; values above 100 are conventionally treated as extreme evidence.
Limitations
- The sample is small (14 firms), and ESG scores were missing for four firms from two providers.
- The authors call for deeper investigation of the implications for public interest and stakeholder theory.
How to cite
Strang, K. D., & Vajjhala, N. R. (2024). Evaluating the Anti-Corruption Factor in Environmental, Social, and Governance Indices by Sampling Large Financial Asset Management Firms. Sustainability, 16(23), 10240. https://doi.org/10.3390/su162310240
BibTeX
@article{strang2024esg,
title = {Evaluating the Anti-Corruption Factor in Environmental, Social, and Governance Indices by Sampling Large Financial Asset Management Firms},
author = {Strang, Kenneth David and Vajjhala, Narasimha Rao},
journal = {Sustainability},
volume = {16},
number = {23},
pages = {10240},
year = {2024},
publisher = {MDPI},
doi = {10.3390/su162310240},
url = {https://doi.org/10.3390/su162310240}
}Related research