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银行贷款的风险管理是关系到整个金融系统稳定的重大问题。本文利用logit方法以及人民银行提供的信贷数据库,根据相关的变量建立模型,并分析了该模型对贷款违约的预测能力。与以前的研究不同,我们的研究着重考虑了违约成本在贷款决策中影响,给予一类、二类错误不同的权重,这样的预测模型能更好地符合银行实际操作的需求。本文的研究也可以作为银行内部风险管理的参考。
The risk management of bank loans is a major issue that affects the stability of the entire financial system. In this paper, using the logit method and the credit database provided by the People’s Bank of China, we build a model based on the relevant variables and analyze the ability of the model to predict the loan default. Different from the previous studies, our research focuses on the impact of default costs on loan decisions, giving different weightings to class I and class II errors. Such a prediction model can better meet the actual needs of banks. The research in this paper can also serve as a reference for the bank’s internal risk management.