运用模糊推理系统对小额信贷过程进行分析支持

Elchin Aliyev, E. Aliyev, A. Ali
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引用次数: 0

摘要

在与他签订贷款协议之前,对申请人获得小额信贷的偿付能力进行全面分析。这样就可以确定与银行贷款无法及时偿还的可能性有关的风险因素,相反,可以评估贷款及时偿还的可能性。因此,评估客户的信誉是商业银行和小额信贷机构确定向一个或另一个申请人发放小额贷款的可能性的工作的一个组成部分。本文提出了一种平衡的方法,以个人偿付能力的多标准评估为基础,除其他外,对其偿付能力指标进行模糊分析。所建立的模糊推理系统与偿债能力评估的统计方法相结合,可以作为信用决策支持系统的分析核心。以10个假设的备选借款人为例,根据其现有指标的特点,对其偿债能力进行了相应的评估,包括评分法、帕累托法、伯德法和模糊推理系统。这种综合方法的特点是能够可靠地识别具有高度信用纪律的一组个人,以及与他们有关的信贷决策被归类为高风险的人的特征。
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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.
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来源期刊
Journal of Automation and Information Sciences
Journal of Automation and Information Sciences AUTOMATION & CONTROL SYSTEMS-
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审稿时长
6-12 weeks
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.
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