A Bibliometric Study on Methodological Approaches of Credit Rating System

This paper aims to study the main trends of scientific research in the credit rating system to clarify methodological approaches, influence factors, and validation, especially in the context of corporate entities. To achieve this goal, this paper focuses on machine learning algorithms, analyzes publications on credit rating in the Web of Science database, covers the period from 2013 to 2022, specifies the research areas, and determines their citation and scientific position. The authors have applied several literature review techniques, a bibliometric citation and co-citation analysis using special program software VOSviewer and R program, and a review of the most cited papers. The analysis results allow us to offer social media as a new component and using support vector machine and neural networks in the creation rating system. This paper can be considered as a contribution to the decision-making process of the financial institutions' future and policymakers in Kazakhstan.