Индекс этичности российских банков на основе искусственного интеллекта

Доклады Российской академии наук. Математика, информатика, процессы управления (ранее - Доклады Академии Наук. Математика). 2024. Т. 520. № 6. С. 70–81.

Storchevoy M., Parshakov P., Paklina S., Buzmakov A. V., Krakovich V.

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 of machine analysis of consumer feedback from Russian banks 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 3,000- 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), with only the BERT model validated and the MFD-based model not. The ethicality index will be useful as an alternative metric to the popular ESG ratings both for theoretical research on company behavior and for practical tasks of managing company reputation and forming policies to regulate the behavior of market participants.

Keywords: искусственный интеллект, ethics, индекс, index, BERT, BERT, этичность, Natural Language Processing (NLP), Natural Language Processing (NLP), artificial intelligence

Publication based on the results of: Measuring and improving the effectiveness of ethics trainings and ethics education courses for Russian university students and managers of Russian companies (2024)