Study on Loan Pricing Model of Commercial Banks Based on Artificial Neural Network

In recent years, commercial banks and other financial institutions have been carrying out unprecedented reforms on the marketization of interest rates, and the floating space of loan interest rates has been constantly expanding. Therefore, loan pricing has become the most critical link of Chinese commercial banks. It is urgent to construct a scientific and objective loan pricing model so as to keep pace with the competition rhythm of commercial banks in developed countries and make the allocation of financial resources in China more optimized and better serve the economic development of China in the new stage. First of all, this paper analyzes the existing loan pricing model of Chinese commercial banks, deeply recognizes the impact of human subjectivity on loan pricing, and then determines that the core index of loan pricing, namely risk rating, should be evaluated by the objective back propagation algorithm, namely BP algorithm. On the basis of these theories and practices, this paper discusses the new loan pricing model of Chinese commercial banks, that is, the loan pricing based on the risk rating classification of BP algorithm, and conducts an empirical analysis with the sample customer data. Finally, it gives relevant recommendations from the macro-external factors and its own internal system on improving the loan pricing to commercial banks.