Credit scoring model for microfinance organizations

- Yaroshchuk, Svitlana O., Shapovalova, Nonna (orcid.org/0000-0001-9146-1205), Striuk, A.M. (orcid.org/0000-0001-9240-1976), Rybalchenko, Olena (orcid.org/0000-0001-8691-5401), Dotsenko, Iryna (orcid.org/0000-0001-7912-2497) and Bilashenko, Svitlana (orcid.org/0000-0002-4331-7425) (2019) Credit scoring model for microfinance organizations Computer Science & Software Engineering. Proceedings of the 2nd Student Workshop (CS&SE@SW 2019), Kryvyi Rih, November 29, 2019 (2546). pp. 115-127. ISSN 1613-0073

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Abstract

The purpose of the work is the development and application of models for scoring assessment of microfinance institution borrowers. This model allows to increase the efficiency of work in the field of credit. The object of research is lending. The subject of the study is a direct scoring model for improving the quality of lending using machine learning methods. The objective of the study: to determine the criteria for choosing a solvent borrower, to develop a model for an early assessment, to create software based on neural networks to determine the probability of a loan default risk. Used research methods such as analysis of the literature on banking scoring; artificial intelligence methods for scoring; modeling of scoring estimation algorithm using neural networks, empirical method for determining the optimal parameters of the training model; method of object-oriented design and programming. The result of the work is a neural network scoring model with high accuracy of calculations, an implemented system of automatic customer lending.

Item Type:	Article
Keywords:	neural network, machine learning, lending, scoring
Subjects:	Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 00 Prolegomena. Fundamentals of knowledge and culture. Propaedeutics > 004 Computer science and technology. Computing. Data processing > 004.9 ІКТ ( Application-oriented computer-based techniques ) Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 3 Social Sciences > 33 Economics. Economic science Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 3 Social Sciences > 37 Education > 378 Higher education. Universities. Academic study
Divisions:	Institute for Digitalisation of Education > Joint laboratory with SIHE “Kryvyi Rih National University”
Depositing User:	Сергій Олексійович Семеріков
Date Deposited:	24 Apr 2020 20:51
Last Modified:	24 Apr 2020 20:51
URI:	https://lib.iitta.gov.ua/id/eprint/720098

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