scholarly journals SME Credit Risk Analysis Using Bank Lending Data: An Analysis of Thai SMEs

Author(s):  
Naoyuki Yoshino ◽  
Farhad Taghizadeh Hesary ◽  
Phadet Charoensivakorn ◽  
Baburam Niraula
2016 ◽  
Vol 15 (3) ◽  
pp. 383-406 ◽  
Author(s):  
Naoyuki Yoshino ◽  
Farhad Taghizadeh-Hesary ◽  
Phadet Charoensivakorn ◽  
Baburam Niraula

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Gang Kou ◽  
Wenshuai Wu

This paper proposes an analytic hierarchy model (AHM) to evaluate classification algorithms for credit risk analysis. The proposed AHM consists of three stages: data mining stage, multicriteria decision making stage, and secondary mining stage. For verification, 2 public-domain credit datasets, 10 classification algorithms, and 10 performance criteria are used to test the proposed AHM in the experimental study. The results demonstrate that the proposed AHM is an efficient tool to select classification algorithms in credit risk analysis, especially when different evaluation algorithms generate conflicting results.


2020 ◽  
pp. 275-348
Author(s):  
Terence M. Yhip ◽  
Bijan M. D. Alagheband

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