ANALYSIS OF SCORING AND RATING MODELS USING NEURAL NETWORKS
Anatoliy Antonov, Ventsislav Nikolov
Pages: 105-118
Published: 12 Sep 2018
Views: 2,724
Downloads: 361
Citations: 1 (Google Scholar)
Abstract: This research paper investigates an approach for analysis of an established system to determine credit rating and scoring, according to regulatory requirements. For this purpose, a model of a neural network is used, on which the realized logic is transferred. According to the properties of the model, sensitivities, significance, independency and other parameters of the input factors are determined.
Keywords: credit rating, scoring, regulatory requirements, analysis of the factors
Cite this article: Anatoliy Antonov, Ventsislav Nikolov. ANALYSIS OF SCORING AND RATING MODELS USING NEURAL NETWORKS. Journal of International Scientific Publications: Economy & Business 12, 105-118 (2018). https://www.scientific-publications.net/en/article/1001723/
Back to the contents of the volume
© 2026 The Author(s). This is an open access article distributed under the terms of the
Creative Commons Attribution License https://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This permission does not cover any third party copyrighted material which may appear in the work requested.
Disclaimer: The Publisher and/or the editor(s) are not responsible for the statements, opinions, and data contained in any published works. These are solely the views of the individual author(s) and contributor(s). The Publisher and/or the editor(s) disclaim any liability for injury to individuals or property arising from the ideas, methods, instructions, or products mentioned in the content.
