A comprehensive method for credit risk assessment of small and medium-sized enterprises based on Asian data

Naoyuki Yoshino, Farhad Taghi Zadeh Hesary

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Due to the asymmetry of information between borrowers that are small and medium-sized enterprises (SMEs) and lenders (banks), many banks consider this sector to be risky. It is crucial for banks to be able to distinguish healthy companies from risky ones in order to reduce their nonperforming assets in the SME sector. If they can do this, lending and financing to SMEs through banks will be easier, with lower collateral requirements and lower interest rates. In this chapter, we provide a scheme originally developed by Yoshino and Taghizadeh-Hesary (2014) for assigning credit ratings to SMEs by employing two statistical analysis techniques - principal component analysis and cluster analysis - using 11 financial ratios of 1,363 SMEs in Asia. If used by financial institutions, this comprehensive and efficient method could enable banks and other lending agencies around the world, especially in Asia, to group SME customers based on financial health, adjust interest rates on loans, and set lending ceilings for each group.

Original languageEnglish
Title of host publicationUnlocking SME Finance in Asia
Subtitle of host publicationRoles of Credit Rating and Credit Guarantee Schemes
PublisherTaylor and Francis
Pages55-71
Number of pages17
ISBN (Electronic)9780429684579
ISBN (Print)9781138353428
DOIs
Publication statusPublished - 2019 Jan 1

Fingerprint

Credit risk
Risk assessment
Small and medium-sized enterprises
Asia
Lending
Interest rates
Financial institutions
Financial ratios
Statistical analysis
Credit rating
Financing
Principal component analysis
Loans
Cluster analysis
Financial health
Asymmetry of information
Assets

ASJC Scopus subject areas

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

Cite this

Yoshino, N., & Taghi Zadeh Hesary, F. (2019). A comprehensive method for credit risk assessment of small and medium-sized enterprises based on Asian data. In Unlocking SME Finance in Asia: Roles of Credit Rating and Credit Guarantee Schemes (pp. 55-71). Taylor and Francis. https://doi.org/10.4324/9780429401060-3

A comprehensive method for credit risk assessment of small and medium-sized enterprises based on Asian data. / Yoshino, Naoyuki; Taghi Zadeh Hesary, Farhad.

Unlocking SME Finance in Asia: Roles of Credit Rating and Credit Guarantee Schemes. Taylor and Francis, 2019. p. 55-71.

Research output: Chapter in Book/Report/Conference proceedingChapter

Yoshino, N & Taghi Zadeh Hesary, F 2019, A comprehensive method for credit risk assessment of small and medium-sized enterprises based on Asian data. in Unlocking SME Finance in Asia: Roles of Credit Rating and Credit Guarantee Schemes. Taylor and Francis, pp. 55-71. https://doi.org/10.4324/9780429401060-3
Yoshino N, Taghi Zadeh Hesary F. A comprehensive method for credit risk assessment of small and medium-sized enterprises based on Asian data. In Unlocking SME Finance in Asia: Roles of Credit Rating and Credit Guarantee Schemes. Taylor and Francis. 2019. p. 55-71 https://doi.org/10.4324/9780429401060-3
Yoshino, Naoyuki ; Taghi Zadeh Hesary, Farhad. / A comprehensive method for credit risk assessment of small and medium-sized enterprises based on Asian data. Unlocking SME Finance in Asia: Roles of Credit Rating and Credit Guarantee Schemes. Taylor and Francis, 2019. pp. 55-71
@inbook{eb5ebf94a8454c048eb9081d110a07ae,
title = "A comprehensive method for credit risk assessment of small and medium-sized enterprises based on Asian data",
abstract = "Due to the asymmetry of information between borrowers that are small and medium-sized enterprises (SMEs) and lenders (banks), many banks consider this sector to be risky. It is crucial for banks to be able to distinguish healthy companies from risky ones in order to reduce their nonperforming assets in the SME sector. If they can do this, lending and financing to SMEs through banks will be easier, with lower collateral requirements and lower interest rates. In this chapter, we provide a scheme originally developed by Yoshino and Taghizadeh-Hesary (2014) for assigning credit ratings to SMEs by employing two statistical analysis techniques - principal component analysis and cluster analysis - using 11 financial ratios of 1,363 SMEs in Asia. If used by financial institutions, this comprehensive and efficient method could enable banks and other lending agencies around the world, especially in Asia, to group SME customers based on financial health, adjust interest rates on loans, and set lending ceilings for each group.",
author = "Naoyuki Yoshino and {Taghi Zadeh Hesary}, Farhad",
year = "2019",
month = "1",
day = "1",
doi = "10.4324/9780429401060-3",
language = "English",
isbn = "9781138353428",
pages = "55--71",
booktitle = "Unlocking SME Finance in Asia",
publisher = "Taylor and Francis",

}

TY - CHAP

T1 - A comprehensive method for credit risk assessment of small and medium-sized enterprises based on Asian data

AU - Yoshino, Naoyuki

AU - Taghi Zadeh Hesary, Farhad

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Due to the asymmetry of information between borrowers that are small and medium-sized enterprises (SMEs) and lenders (banks), many banks consider this sector to be risky. It is crucial for banks to be able to distinguish healthy companies from risky ones in order to reduce their nonperforming assets in the SME sector. If they can do this, lending and financing to SMEs through banks will be easier, with lower collateral requirements and lower interest rates. In this chapter, we provide a scheme originally developed by Yoshino and Taghizadeh-Hesary (2014) for assigning credit ratings to SMEs by employing two statistical analysis techniques - principal component analysis and cluster analysis - using 11 financial ratios of 1,363 SMEs in Asia. If used by financial institutions, this comprehensive and efficient method could enable banks and other lending agencies around the world, especially in Asia, to group SME customers based on financial health, adjust interest rates on loans, and set lending ceilings for each group.

AB - Due to the asymmetry of information between borrowers that are small and medium-sized enterprises (SMEs) and lenders (banks), many banks consider this sector to be risky. It is crucial for banks to be able to distinguish healthy companies from risky ones in order to reduce their nonperforming assets in the SME sector. If they can do this, lending and financing to SMEs through banks will be easier, with lower collateral requirements and lower interest rates. In this chapter, we provide a scheme originally developed by Yoshino and Taghizadeh-Hesary (2014) for assigning credit ratings to SMEs by employing two statistical analysis techniques - principal component analysis and cluster analysis - using 11 financial ratios of 1,363 SMEs in Asia. If used by financial institutions, this comprehensive and efficient method could enable banks and other lending agencies around the world, especially in Asia, to group SME customers based on financial health, adjust interest rates on loans, and set lending ceilings for each group.

UR - http://www.scopus.com/inward/record.url?scp=85071821317&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85071821317&partnerID=8YFLogxK

U2 - 10.4324/9780429401060-3

DO - 10.4324/9780429401060-3

M3 - Chapter

AN - SCOPUS:85071821317

SN - 9781138353428

SP - 55

EP - 71

BT - Unlocking SME Finance in Asia

PB - Taylor and Francis

ER -