Credit risk: estimating loss frequencies and loss

向各种公司和个人放贷是银行的核心业务。这种贷款活动伴随着信用风险，即一些借款人违约并无法支付所需款项的风险。准确估计信用风险是银行风险管理的重要内容。在这个项目中，我们改进了违约客户的损失频率和损失率之间的相关性的模型。这种依赖的原因来自潜在的经济周期：与经济繁荣时期相比，在经济低迷时期，亏损发生的频率和程度都更高。我们为损失频率和损失率之间的这种相关性结构建立的模型将有助于更准确地估计信用风险，从而更准确地确定资本需求。

Lending to various companies and individuals is a core business of banks. This lending activity comes with credit risk, namely the risk that some borrowers default and fail to make required payments. Estimating credit risk accurately is important for banks' risk management. In this project, we improve the modelling of the dependence between loss frequency and loss rate of defaulting customers. The reason for the dependence comes from the underlying economic cycle: in an economic downturn, losses occur both more frequently and more severely than in an economic boom. Our proposed modelling for this dependence structure between loss frequency and loss rate will help estimate credit risk more accurately and thus determine capital requirements more precisely.