A stable credit rating model based on learning vector quantization

2011 ◽  
Vol 15 (2) ◽  
pp. 237-250 ◽  
Author(s):  
Ning Chen ◽  
Armando Vieira ◽  
Bernardete Ribeiro ◽  
João Duarte ◽  
João Neves
Keyword(s):  
Vector Quantization ◽  
Credit Rating ◽  
Learning Vector Quantization ◽  
Model Based ◽  
Rating Model

scholarly journals An Optimal Decision Assessment Model Based on the Acceptable Maximum LGD of Commercial Banks and Its Application

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Baofeng Shi ◽  
Bin Meng ◽  
Jing Wang
Keyword(s):  
Commercial Banks ◽  
Risk Evaluation ◽  
Credit Rating ◽  
Assessment Method ◽  
Assessment Model ◽  
Optimal Decision ◽  
Constraint Condition ◽  
Loss Given Default ◽  
Model Based ◽  
Rating Model

This paper introduces a novel decision assessment method which is suitable for customers’ credit risk evaluation and credit decision. First of all, the paper creates an optimal credit rating model, and it consisted of an objective function and two constraint conditions. The first constraint condition of the strictly increasing LGDs eliminates the unreasonable phenomenon that the higher the credit rating is, the higher the LGD (loss given default) is. Secondly, on the basis of the credit rating results, a credit decision-making assessment model based on measuring the acceptable maximum LGD of commercial banks is established. Thirdly, empirical results using the data on 2817 farmers’ microfinance of a Chinese commercial bank suggest that the proposed approach can accurately find out the good customers from all the loan applications. Moreover, our approach contributes to providing a reference for decision assessment of customers in other commercial banks in the world.

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