By studying the model problems in corporate credit assessment, information support is provided for corporate business activities and decision-making processes. A credit assessment model based on an improved BP neural network is proposed. On the basis of establishing an indicator system and an output mechanism, the design and implementation of an assessment system based on a credit assessment model are discussed. Keywords: BP neural network; credit assessment; indicator system; assessment system Credit risk prediction and risk control are important aspects of modern enterprise management. In many countries, the banking crisis caused by non-performing loans is quite serious. Therefore, strengthening corporate credit risk management, establishing and improving the risk management system within banks and enterprises, providing a scientific reference for bank decision-making, and comprehensively preventing and resolving financial risks are the main tasks currently faced by banks and enterprises. To this end, the author designed a credit assessment model based on an improved BP neural network, making the assessment model dynamic through a flexible set of relevant indicator systems and a credit assessment model library dynamically generated for various users.
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