Research on algorithms development and optimization for personal credit scoring

In order to effectively recognize and measure individual credit risk and avoid the negative impact which financial crisis has on the commercial banks, and thus keep the normal operation of the credit and financial markets in China, this paper summarizes the main model of personal credit scoring and its development, and also clarifies the validity and integrity of the credit samples, the rationality of the index system and the selection, applicability of the model in the study of personal credit rating. In view of this, based on correlation analysis, early warning of abnormal samples can be achieved, and the samples are complemented through the Monte Carlo Algorithm. Combined with the statistical model and artificial intelligence model, the index system is optimized and given respective significant weight through traversal algorithm. With accuracy, robustness, first misjudgment rate, second misjudgment rate and difference as the selection index, the selection and output of the scoring model can be realized. Through the above optimization algorithm, the problem in personal credit scoring is solved, and the risk control ability of commercial banks is improved as well.