Research on Assessment Method for Credit Risk in Commercial Banks of China Based on Data Mining

Abstract:

Due to the huge loss to the bank caused by credit risk in the financial debt crisis of the international Banking industry in 1980s, the research on Credit Assessment Methods is becoming the central issue of the study of financial theory in China and abroad. This paper builded the assets financial evaluation system of credit risk level based on the association rules-Apriori algorithm of data mining technology, which aimed the problems and the serious shortage of risk quantification study in domestic banks credit risk management. At the same time, taking into account the actual situation of our country, this paper analyzed that there are certain difficulties to use modern credit risk measurement models to evaluation the credit risk of commercial banks. And it suggests building a credit portfolio risk measurement model suitable for China's commercial banks with using logistic regression model of data mining technology.

• Periodical: Applied Mechanics and Materials (Volumes 303-306)
• Pages: 1361-1364
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.303-306.1361
• Online since: February 2013
• Authors: Wen Juan Li, Shi Min Wang
• Keywords: Apriori Algorithm, Credit Risk, Data Mining (DM), Evaluation Index, Logistic Regression

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