基于大数据征信的商业银行信贷风险管理研究

Research on Credit Risk Management of Commercial Banks Based on Big Data Credit Investigation

近年来,伴随着金融科技快速崛起,商业银行对大数据的应用越发重视和不断加强。商业银行通过应用大数据模型,对客户进行精准画像,逐步在信贷客户筛选、产品设计、风险防控等方面推广使用。本文从人民银行征信管理的视角,全面分析了商业银行在个人、小微企业和对公客户方面的大数据信贷模式,客观评估了商业银行大数据信贷的运用现状,认真梳理了商业银行在应用大数据信贷风控的实践中存在着数据来源渠道窄、产品同质化高、应用模型不透明、平台建设缓慢、缺乏有效监管等痛点和难点。为此从防范化解信贷风险和支持业务创新角度出发,建议从完善大数据征信法规制度、优化征信信息与产品服务、搭建多层次征信平台体系和规范大数据应用监管等方面支持发展大数据信贷业务。

In recent years,with the rapid rise of financial technology,commercial banks have paid more and more attention to and strengthened the application of big data.Commercial banks use big data models to accurately profile customers,and gradually promote their use in credit customer screening,product design,and risk prevention and control.From the perspective of credit management of the People’s Bank of China,this article comprehensively analyzes the big data credit model of commercial banks for individuals,small and micro enterprises and corporate customers,objectively evaluates the current status and positive significance of the use of big data credit by commercial banks,and carefully sorts out the business In the practice of applying big data credit risk control,banks have pain points and difficulties such as narrow data source channels,high product homogeneity,opaque application models,slow platform construction,and lack of effective supervision.To this end,from the perspective of preventing and dissolving credit risks and supporting business innovation,it is recommended to encourage support in terms of improving big data credit reporting laws and regulations,optimizing credit reporting information and product services,building a multi-level credit reporting platform system,and standardizing big data application supervision.Commercial bank credit business development.