Credit risk analysis of small and medium-sized enterprises based on Thai data

Farhad Taghizadeh‐Hesary, N. Yoshino, Phadet Charoensivakorn, Baburam Niraula
{"title":"Credit risk analysis of small and medium-sized enterprises based on Thai data","authors":"Farhad Taghizadeh‐Hesary, N. Yoshino, Phadet Charoensivakorn, Baburam Niraula","doi":"10.4324/9780429401060-6","DOIUrl":null,"url":null,"abstract":"SMEs often have severe difficulties raising money. Considering the bank-dominated characteristic of economies in Asia, banks are the main source of financing. In order to prevent the accumulation of non-performing loans in the small and medium-sized enterprise (SME) sector, it is crucial for banks to distinguish healthy SMEs from risky ones. This chapter examines how a credit rating scheme for SMEs can be developed when access to other financial and non-financial ratios is not possible by using data on lending by banks to SMEs. We employ statistical techniques on five variables from a sample of 3,272 Thai SMEs and classify them into subgroups based on their financial health. The source of data used for the credit risk analysis in this research is the National Credit Bureau of Thailand. By employing these techniques, banks could reduce information asymmetry and consequently set interest rates and lending ceilings for SMEs. This would ease financing to healthy SMEs and reduce the number of non-performing loans to this important sector.","PeriodicalId":273088,"journal":{"name":"Unlocking SME Finance in Asia","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Unlocking SME Finance in Asia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4324/9780429401060-6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

SMEs often have severe difficulties raising money. Considering the bank-dominated characteristic of economies in Asia, banks are the main source of financing. In order to prevent the accumulation of non-performing loans in the small and medium-sized enterprise (SME) sector, it is crucial for banks to distinguish healthy SMEs from risky ones. This chapter examines how a credit rating scheme for SMEs can be developed when access to other financial and non-financial ratios is not possible by using data on lending by banks to SMEs. We employ statistical techniques on five variables from a sample of 3,272 Thai SMEs and classify them into subgroups based on their financial health. The source of data used for the credit risk analysis in this research is the National Credit Bureau of Thailand. By employing these techniques, banks could reduce information asymmetry and consequently set interest rates and lending ceilings for SMEs. This would ease financing to healthy SMEs and reduce the number of non-performing loans to this important sector.
基于泰国数据的中小企业信用风险分析
中小企业往往在融资方面遇到严重困难。考虑到亚洲经济以银行为主导的特点,银行是主要的融资来源。为了防止中小企业不良贷款的积累,银行区分健康中小企业和风险中小企业是至关重要的。本章探讨了在无法利用银行对中小企业的贷款数据获得其他财务和非财务比率的情况下,如何为中小企业制定信用评级计划。我们对来自3,272家泰国中小企业样本的五个变量采用统计技术,并根据其财务健康状况将其分类为子组。本研究用于信用风险分析的数据来源是泰国国家信用局。通过采用这些技术,银行可以减少信息不对称,从而为中小企业设定利率和贷款上限。这将减轻对健康中小企业的融资压力,并减少这一重要部门的不良贷款数量。
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
自引率
0.00%
发文量
0
×
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