大数据背景下商业银行信贷风险研究

On Credit Risk of Commercial Banks under the Background of Big Data

随着大数据等新兴技术在各个领域的广泛应用,人类社会已经进入了“大数据”信息时代。在“大数据”信息时代,商业银行传统信贷风险管理模式存在许多问题,通过数字化转型可以有效解决这些问题,降低信贷风险,因此,数字化转型程度已成为衡量商业银行竞争力的核心指标。中国银行在数字化转型之前也存在一些问题,如内部控制薄弱、信贷管理存在隐患、内部控制不完善等,导致其信贷管理风险增加。针对上述问题及产生问题的原因,中国银行利用大数据,采取建立新型违约模型、更新信贷业务流程等措施,进行实时贷后风险监管,取得了良好效果。

With the wide application of new technologies such as big data in various fields,human society has entered the“Big Data”information age.In the“Big Data”information age,there are many problems in the traditional credit risk management model of com⁃mercial banks,which can be effectively solved by digital transformation to reduce credit risk.Therefore,the degree of digital transfor⁃mation has become a core indicator to measure the competitiveness of commercial banks.Taking the Bank of China as an example,we analyze the problems faced by the bank before its digital transformation,that is,weak internal control,hidden trouble in credit manage⁃ment,imperfect internal control leading to an increase in credit management risk,and the reason for it.To solve the above problems,Bank of China uses big data to build a new default model,update credit business processes,real-time post-loan risk supervision,and achieved good results.