{"title":"运用模糊推理系统对小额信贷过程进行分析支持","authors":"Elchin Aliyev, E. Aliyev, A. Ali","doi":"10.34229/1028-0979-2021-4-5","DOIUrl":null,"url":null,"abstract":"A comprehensive analysis of the applicantʼs solvency for obtaining a microcredit precedes the conclusion of a loan agreement with him. This allows to determine the risk factors associated with the possibility of non-repayment of a bank loan in due time, and, on the contrary, to assess the likelihood of timely repayment of the loan. Therefore, the assessment of the clientʼs creditworthiness is an integral part of the work of commercial banks and microfinance organizations to determine the possibility of issuing microloans to one or another applicant. The paper proposes a balanced approach to the multi-criteria assessment of the solvency of individuals, based, among other things, on a fuzzy analysis of their solvency indicators. The developed fuzzy inference system in combination with statistical methods for assessing solvency, can serve as an analytical core for a credit decision support system. Based on the example of ten hypothetical alternative borrowers, characterized by their current indicators, the corresponding assessments of their solvency were made, including scoring, Pareto method, Bord method and using a fuzzy inference system. Such a combined approach is distinguished by the ability to identify reliably a group of individuals with high credit discipline and the characteristics of those in relation to whom credit decisions are classified as high-risk.","PeriodicalId":54874,"journal":{"name":"Journal of Automation and Information Sciences","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"ANALYTICAL SUPPORT OF THE MICROCREDITING PROCESS USING A FUZZY INFERENCE SYSTEM\",\"authors\":\"Elchin Aliyev, E. Aliyev, A. Ali\",\"doi\":\"10.34229/1028-0979-2021-4-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A comprehensive analysis of the applicantʼs solvency for obtaining a microcredit precedes the conclusion of a loan agreement with him. This allows to determine the risk factors associated with the possibility of non-repayment of a bank loan in due time, and, on the contrary, to assess the likelihood of timely repayment of the loan. Therefore, the assessment of the clientʼs creditworthiness is an integral part of the work of commercial banks and microfinance organizations to determine the possibility of issuing microloans to one or another applicant. The paper proposes a balanced approach to the multi-criteria assessment of the solvency of individuals, based, among other things, on a fuzzy analysis of their solvency indicators. The developed fuzzy inference system in combination with statistical methods for assessing solvency, can serve as an analytical core for a credit decision support system. Based on the example of ten hypothetical alternative borrowers, characterized by their current indicators, the corresponding assessments of their solvency were made, including scoring, Pareto method, Bord method and using a fuzzy inference system. Such a combined approach is distinguished by the ability to identify reliably a group of individuals with high credit discipline and the characteristics of those in relation to whom credit decisions are classified as high-risk.\",\"PeriodicalId\":54874,\"journal\":{\"name\":\"Journal of Automation and Information Sciences\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Automation and Information Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.34229/1028-0979-2021-4-5\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Automation and Information Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.34229/1028-0979-2021-4-5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
ANALYTICAL SUPPORT OF THE MICROCREDITING PROCESS USING A FUZZY INFERENCE SYSTEM
A comprehensive analysis of the applicantʼs solvency for obtaining a microcredit precedes the conclusion of a loan agreement with him. This allows to determine the risk factors associated with the possibility of non-repayment of a bank loan in due time, and, on the contrary, to assess the likelihood of timely repayment of the loan. Therefore, the assessment of the clientʼs creditworthiness is an integral part of the work of commercial banks and microfinance organizations to determine the possibility of issuing microloans to one or another applicant. The paper proposes a balanced approach to the multi-criteria assessment of the solvency of individuals, based, among other things, on a fuzzy analysis of their solvency indicators. The developed fuzzy inference system in combination with statistical methods for assessing solvency, can serve as an analytical core for a credit decision support system. Based on the example of ten hypothetical alternative borrowers, characterized by their current indicators, the corresponding assessments of their solvency were made, including scoring, Pareto method, Bord method and using a fuzzy inference system. Such a combined approach is distinguished by the ability to identify reliably a group of individuals with high credit discipline and the characteristics of those in relation to whom credit decisions are classified as high-risk.
期刊介绍:
This journal contains translations of papers from the Russian-language bimonthly "Mezhdunarodnyi nauchno-tekhnicheskiy zhurnal "Problemy upravleniya i informatiki". Subjects covered include information sciences such as pattern recognition, forecasting, identification and evaluation of complex systems, information security, fault diagnosis and reliability. In addition, the journal also deals with such automation subjects as adaptive, stochastic and optimal control, control and identification under uncertainty, robotics, and applications of user-friendly computers in management of economic, industrial, biological, and medical systems. The Journal of Automation and Information Sciences will appeal to professionals in control systems, communications, computers, engineering in biology and medicine, instrumentation and measurement, and those interested in the social implications of technology.