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

Farhad Taghi Zadeh Hesary, Naoyuki Yoshino, Phadet Charoensivakorn, Baburam Niraula

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Small and medium-sized enterprise (SMEs) often face severe difficulties raising money. Considering the bank-dominated characteristic of Asian economies, banks are the main source of financing. In order to prevent the accumulation of nonperforming loans in the 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 financial and non-financial data are not accessible just by using lending data of 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 nonperforming loans to this important sector.

Original languageEnglish
Title of host publicationUnlocking SME Finance in Asia
Subtitle of host publicationRoles of Credit Rating and Credit Guarantee Schemes
PublisherTaylor and Francis
Pages112-135
Number of pages24
ISBN (Electronic)9780429684579
ISBN (Print)9781138353428
DOIs
Publication statusPublished - 2019 Jan 1

Fingerprint

Credit risk
Risk analysis
Small and medium-sized enterprises
Financing
Lending
Non-performing loans
Interest rates
Thailand
Information asymmetry
Credit rating
Asian economies
Credit
Financial health

ASJC Scopus subject areas

  • Economics, Econometrics and Finance(all)
  • Business, Management and Accounting(all)

Cite this

Taghi Zadeh Hesary, F., Yoshino, N., Charoensivakorn, P., & Niraula, B. (2019). Credit risk analysis of small and medium-sized enterprises based on thai data. In Unlocking SME Finance in Asia: Roles of Credit Rating and Credit Guarantee Schemes (pp. 112-135). Taylor and Francis. https://doi.org/10.4324/9780429401060-6

Credit risk analysis of small and medium-sized enterprises based on thai data. / Taghi Zadeh Hesary, Farhad; Yoshino, Naoyuki; Charoensivakorn, Phadet; Niraula, Baburam.

Unlocking SME Finance in Asia: Roles of Credit Rating and Credit Guarantee Schemes. Taylor and Francis, 2019. p. 112-135.

Research output: Chapter in Book/Report/Conference proceedingChapter

Taghi Zadeh Hesary, F, Yoshino, N, Charoensivakorn, P & Niraula, B 2019, Credit risk analysis of small and medium-sized enterprises based on thai data. in Unlocking SME Finance in Asia: Roles of Credit Rating and Credit Guarantee Schemes. Taylor and Francis, pp. 112-135. https://doi.org/10.4324/9780429401060-6
Taghi Zadeh Hesary F, Yoshino N, Charoensivakorn P, Niraula B. Credit risk analysis of small and medium-sized enterprises based on thai data. In Unlocking SME Finance in Asia: Roles of Credit Rating and Credit Guarantee Schemes. Taylor and Francis. 2019. p. 112-135 https://doi.org/10.4324/9780429401060-6
Taghi Zadeh Hesary, Farhad ; Yoshino, Naoyuki ; Charoensivakorn, Phadet ; Niraula, Baburam. / Credit risk analysis of small and medium-sized enterprises based on thai data. Unlocking SME Finance in Asia: Roles of Credit Rating and Credit Guarantee Schemes. Taylor and Francis, 2019. pp. 112-135
@inbook{c75d41ae6627402b9fb99c7a9c1d74a7,
title = "Credit risk analysis of small and medium-sized enterprises based on thai data",
abstract = "Small and medium-sized enterprise (SMEs) often face severe difficulties raising money. Considering the bank-dominated characteristic of Asian economies, banks are the main source of financing. In order to prevent the accumulation of nonperforming loans in the 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 financial and non-financial data are not accessible just by using lending data of 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 nonperforming loans to this important sector.",
author = "{Taghi Zadeh Hesary}, Farhad and Naoyuki Yoshino and Phadet Charoensivakorn and Baburam Niraula",
year = "2019",
month = "1",
day = "1",
doi = "10.4324/9780429401060-6",
language = "English",
isbn = "9781138353428",
pages = "112--135",
booktitle = "Unlocking SME Finance in Asia",
publisher = "Taylor and Francis",

}

TY - CHAP

T1 - Credit risk analysis of small and medium-sized enterprises based on thai data

AU - Taghi Zadeh Hesary, Farhad

AU - Yoshino, Naoyuki

AU - Charoensivakorn, Phadet

AU - Niraula, Baburam

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Small and medium-sized enterprise (SMEs) often face severe difficulties raising money. Considering the bank-dominated characteristic of Asian economies, banks are the main source of financing. In order to prevent the accumulation of nonperforming loans in the 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 financial and non-financial data are not accessible just by using lending data of 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 nonperforming loans to this important sector.

AB - Small and medium-sized enterprise (SMEs) often face severe difficulties raising money. Considering the bank-dominated characteristic of Asian economies, banks are the main source of financing. In order to prevent the accumulation of nonperforming loans in the 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 financial and non-financial data are not accessible just by using lending data of 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 nonperforming loans to this important sector.

UR - http://www.scopus.com/inward/record.url?scp=85071824419&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85071824419&partnerID=8YFLogxK

U2 - 10.4324/9780429401060-6

DO - 10.4324/9780429401060-6

M3 - Chapter

AN - SCOPUS:85071824419

SN - 9781138353428

SP - 112

EP - 135

BT - Unlocking SME Finance in Asia

PB - Taylor and Francis

ER -