Credit strategy of micro, small, and medium enterprises with known reputation risk: Evidence from a comprehensive evaluation model

IF 1.1 Q3 INFORMATION SCIENCE & LIBRARY SCIENCE
Wanting Chen, Xuanyi Wu, Z. Y. Chen, Y. Meng, Ruei-yuan Wang, Timothy Chen
{"title":"Credit strategy of micro, small, and medium enterprises with known reputation risk: Evidence from a comprehensive evaluation model","authors":"Wanting Chen, Xuanyi Wu, Z. Y. Chen, Y. Meng, Ruei-yuan Wang, Timothy Chen","doi":"10.47974/jios-1183","DOIUrl":null,"url":null,"abstract":"With poor financial information transparency, and relatively weak profitability and asset strength stability, Small, medium and micro enterprises started late in China. This makes commercial banks need to bear more risks when providing loans to small, medium and micro enterprises than large enterprises. Big. When commercial banks do not have credit records of certain small, medium and micro enterprises, this will increase the risk that banks need to bear when lending to these small, medium and micro enterprises without credit records, and will also increase the difficulty of credit loan for small, medium and micro enterprises in commercial banks.First of all, we should comprehensively analyze the credit risk of enterprises, establish the TOPSIS comprehensive evaluation model, and then establish the constraint conditions according to the data given by the topic, calculate the interest rate of bank loans to each type of enterprises, so as to determine the bank’s credit strategy. The paper seeks the bank’s credit strategy for these enterprises when the annual total amount of credit is fixed. We use AHP (Analytic Hierarchy Process) to normalize the credit rating, and then get the relevant data ranking of enterprises with credit records through TOPSIS comprehensive evaluation model. Through cluster analysis, we divide them into nine categories, and make the optimal credit strategy from the perspective of interest rate and credit line.","PeriodicalId":46518,"journal":{"name":"JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES","volume":null,"pages":null},"PeriodicalIF":1.1000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47974/jios-1183","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 0

Abstract

With poor financial information transparency, and relatively weak profitability and asset strength stability, Small, medium and micro enterprises started late in China. This makes commercial banks need to bear more risks when providing loans to small, medium and micro enterprises than large enterprises. Big. When commercial banks do not have credit records of certain small, medium and micro enterprises, this will increase the risk that banks need to bear when lending to these small, medium and micro enterprises without credit records, and will also increase the difficulty of credit loan for small, medium and micro enterprises in commercial banks.First of all, we should comprehensively analyze the credit risk of enterprises, establish the TOPSIS comprehensive evaluation model, and then establish the constraint conditions according to the data given by the topic, calculate the interest rate of bank loans to each type of enterprises, so as to determine the bank’s credit strategy. The paper seeks the bank’s credit strategy for these enterprises when the annual total amount of credit is fixed. We use AHP (Analytic Hierarchy Process) to normalize the credit rating, and then get the relevant data ranking of enterprises with credit records through TOPSIS comprehensive evaluation model. Through cluster analysis, we divide them into nine categories, and make the optimal credit strategy from the perspective of interest rate and credit line.
已知声誉风险的中小微企业信用策略:来自综合评价模型的证据
中国中小微企业起步较晚,财务信息透明度较差,盈利能力和资产实力稳定性相对较弱。这使得商业银行在向中小微企业提供贷款时比向大企业提供贷款时需要承担更多的风险。大了。当商业银行没有对某些中小微企业的信用记录时,这将增加银行在向这些没有信用记录的中小微企业提供贷款时需要承担的风险,也将增加商业银行对中小微企业的信用贷款难度。首先对企业的信用风险进行综合分析,建立TOPSIS综合评价模型,然后根据课题给出的数据建立约束条件,计算出银行对各类企业的贷款利率,从而确定银行的信贷策略。本文探讨了在年度信贷总额一定的情况下,银行对这些企业的信贷策略。采用层次分析法对信用评级进行归一化,然后通过TOPSIS综合评价模型得到有信用记录企业的相关数据排名。通过聚类分析,将其分为九类,并从利率和授信额度的角度制定最优信贷策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES
JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES INFORMATION SCIENCE & LIBRARY SCIENCE-
自引率
21.40%
发文量
88
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信