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Research on BP Neural Network Evaluation Model of Credit Risk of Bank Clients

机译:银行客户信用风险的BP神经网络评估模型研究

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Credit is the cornerstone of modern market economy. Credit risk is one of the most important risks which the banks are facing to. Credit risk Evaluation virtually is a non-linear classification matter. The banks evaluate and classify the clients according to their information data, then according to the results of classification to decide whether to authorize the loans. This article established the artificial BP neural network evaluation model and achieved intelligence of the bank's credit risk assessment and increased the scientific of bank credit evaluation and management. It is very significant that using trade credit division to determine the credit rating for dealing with bank's non-linear complicated credit management. And we select part of the clients' information of several banks' real estate industry to establish the evaluation model for the empirical test.
机译:信用是现代市场经济的基石。信用风险是银行面临的最重要的风险之一。信用风险评估实际上是非线性分类问题。银行根据客户的信息数据对客户进行评估和分类,然后根据分类结果决定是否批准贷款。本文建立了人工BP神经网络评估模型,实现了银行信用风险评估的智能化,提高了银行信用评估与管理的科学性。使用贸易信用划分来确定信用等级对于处理银行的非线性复杂信用管理具有非常重要的意义。然后,我们从多家银行的房地产行业的客户信息中选择一部分,以建立实证检验的评估模型。

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