Credit risk: estimating loss frequencies and loss

信用风险：估计损失频率和损失

• 批准号: 549168-2019
• 负责人: Frei, Christoph
• 金额: $ 2.19万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=700605
• 关键词: Credit; risk; estimating; loss; frequencies

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.

向各种公司和个人提供贷款是银行的核心业务。这种借贷活动伴随着信用风险，即一些借款人违约和未能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依赖关系的建模。这种依赖性的原因来自于潜在的经济周期：在经济衰退时期，损失的发生比经济繁荣时期更频繁，也更严重。我们建议的模型之间的损失频率和损失率的依赖结构将有助于更准确地估计信用风险，从而更准确地确定资本要求。