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Doklady Rossijskoj Akademii Nauk. Mathematika, Informatika, Processy Upravlenia, 2024, Volume 520, Number 1, Pages 70–81 DOI: https://doi.org/10.31857/S2686954324060111
(Mi danma579)
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INFORMATICS
Ai-based ethics index of Russian banks
M. A. Storchevoya, P. A. Parshakovbc, S. N. Paklinab, A. V. Buzmakovb, V. V. Krakovichab a St. Petersburg School of Economics and Management, National Research University Higher School of Economics, St. Petersburg, Russia
b International Laboratory of Intangible-Driven Economy, National Research University Higher School of Economics, Perm, Russia
c Moscow School of Management SKOLKOVO, Moscow, Russia
DOI:
https://doi.org/10.31857/S2686954324060111
Abstract:
Measuring a company’s ethics is an important element in the mechanism of regulating the behavior of market participants, as it allows consumers and regulators to make better decisions, which has a disciplining effect on companies. We tested various methods for machine analysis of feedback from Russian bank consumers and developed an ethics index that allows us to calculate a quantitative assessment of the ethics of three hundred Russian banks based on consumer feedback for different time periods from 2005 to 2022. We used a bag-of-words method based on the Moral Foundations Dictionary (MFD) and BERT model training based on a 3000- and 10 000-sentence sample marked up by experts. The resulting index was validated based on the number of arbitration cases from 2005 to 2022 (more ethical companies are involved in fewer arbitration cases as a defendant). As a result, only the BERT model was validated, whereas the MFD-based model was not. The ethics index would be useful as a metric alternative to popular ESG ratings for both theoretical research on company behavior and practical tasks of managing company reputation and forming policies of regulating the behavior of market participants.
Keywords:
index, ethics, artificial intelligence, NLP, BERT.
Citation:
M. A. Storchevoy, P. A. Parshakov, S. N. Paklina, A. V. Buzmakov, V. V. Krakovich, “Ai-based ethics index of Russian banks”, Dokl. RAN. Math. Inf. Proc. Upr., 520:1 (2024), 70–81; Dokl. Math., 110:3 (2024), 511–520
Linking options:
https://www.mathnet.ru/eng/danma579 https://www.mathnet.ru/eng/danma/v520/i1/p70
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