The BP neural networks applications in bank credit risk management system

Author(s):  
Shu-Fang Zhao ◽  
Li-Chao Chen
Author(s):  
Ning Yida ◽  
Luo Hehua

As the largest commercial bank in China, ICBC is a typical representative of the electronic business of SMEs. However, the electronic business for SMEs has credit risks and needs to continuously strengthen the credit risk management for SMEs. By analyzing the organization structure, system and process of credit risk management for SME in ICBC, this paper attempts to conclude that there are flaws on credit risk organization structure, credit risk management process and system is not sound enough, and there are omissions before, on and after the loan, in addition, risk management awareness is not strong. In view of the above problems, this paper puts forward some countermeasures and suggestions to improve the organization structure of credit risk management, perfect the credit risk management system of SME, strictly carry out risk control before, during and after loans, and strengthen the consciousness of risk management. Researching the credit risk management system for SMEs in ICBC has a great educational and practical significance, for other commercial banks establishing and improving their risk management system.


2008 ◽  
Vol 3 (3) ◽  
pp. 323-332 ◽  
Author(s):  
Evelyn Richard ◽  
Marcellina Chijoriga ◽  
Erasmus Kaijage ◽  
Christer Peterson ◽  
Hakan Bohman

2014 ◽  
Vol 20 (4) ◽  
Author(s):  
Lucia Del Chicca ◽  
Gerhard Larcher

AbstractIn this paper we analyze and compare the use of Monte Carlo, quasi-Monte Carlo and hybrid Monte Carlo methods in the credit risk management system “Credit Metrics” by J. P. Morgan. We show that hybrid sequences, used suitably for simulations, perform better, in many relevant situations, than pure Monte Carlo and pure quasi-Monte Carlo methods, and they only rarely perform worse than these methods.


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