Applied Research of Genetic Algorithm in Personal Credit Risk Combined Assessment

Li SHUAI, Tingting LI, Chao XU, Zongfang ZHOU

Abstract


With the increasing scale of individual credit consumption, the individual credit risk assessment has become more and more important. This paper selected 640 samples from the Germany personal credit database as study object. First, this preliminary screened the primitive indexes, and then used sample classification accuracy as fitness function, making combined assessment model based on linear regression and logistic regression through genetic algorithm. The results showed that the combined assessment model based on genetic algorithm had higher accuracy compared to a single model, and combined assessment model based on the least sum of square error had an advantage in the individual credit risk assessment over the others.


Keywords


Personal credit risk assessment; Genetic algorithm; Logistic regression; Combined assessment

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References


Chen, H. Y., & Xu, Y. S. (2000). The estimation of weight of combined prediction and its significance test. Operations Research and Management Science, (2), 75-78.

Fogarty, T. C., & Ireson, N. I. (1993). Evolving Bayesian classifiers for credit control: A comparison with other machine learning methods. Proceedings of the 3rd IMA Conference on Credit Scoring and Credit Control (Vol.5, pp.63-76).

Huang, H. Z., Zhou, Z. F., & Yu, J. K. (2010). ILMBP neural network model and its application in personal credit valuation. Managerialist, (10).

Jiang, M. H. (2006). Research of the combination forecast method of individual credit evaluation for commercial bank (Doctoral dissertation). Retrieved from CNKI (http://cdmd.cnki.com.cn/Article/CDMD-10213-2007040225.htm). (In Chinese).

Jiang, M. H., & Chen, Y. F. (2006). Combining forecasts of personal credit scoring based on RBF neural network. Journal of Harbin Engineering University, 27(z1). (In Chinese).

Lei, Y. J., Zhang, S. W., & Li, X. W. (2004). MATLAB genetic algorithm toolbox and its application. Xi’an: Xidian University Press. (In Chinese).

Liang, S. D., Guo, B., Li, Y., & Fang, Z. B. (2002). Comparative analysis of credit risk model. China Management Science, 10(1), 17-22. (In Chinese).

Ma, Y. K., & Tang, X. W. (1998). Research of the optimization of linear combined prediction model. Systems Engineering-Theory & Practice, (9), 110-115. (In Chinese).

Shi, Q. Y., & Jin, Y. H. (2004). Comparative research of the application of multiple personal credit rating model in China. Statistic Research, (6), 43-47. (In Chinese).

Zhou, Z. F., et al. (2010). The study of the evolution mechanism and valuation method of emerging technology enterprise. Beijing: Science Press.

Zhu, X. D., & Feng, T. J. (2003). Personal credit valuation based on GA neural network. Systems Engineering-Theory & Practice, (12), 34-38. (In Chinese).




DOI: http://dx.doi.org/10.3968/j.mse.1913035X20130703.2416

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