科技赋能背景下的票据贴现客户风险画像研究

Researching the Risk Portrait of Bill Discounting Customers

票据具有成本低、融资便利等特点,是与中小微企业联系最为紧密的金融工具之一。面对"科技赋能+金融生态"深度融合的数字化转型挑战,商业银行纷纷重塑风险管理模式,构建全面化、智能化、现代化的风险管理体系。本文运用社会网络分析方法与K-Means无监督机器学习模型,通过延展单一客户风险特征边界,对客户进行聚类分析。深度刻画客户企业风险全貌,生成立体式客户风险画像,可以将风险管控端口前移,实现全流程闭环风险管理,赋能商业银行精准营销。

Bills are the financial instruments most closely associated with small and medium sized enterprises. Faced with the digital transformation challenge of deep integration of "technology empowerment and financial ecology", commercial banks have reshaped their risk management model and built a comprehensive, intelligent and modern risk management system. In this paper, the social network analysis method and the K-Means unsupervised machine-learning model are used to cluster customers by extending the risk characteristics boundary of any single customer. Depicting the overall picture of customer enterprise risks and generating a three-dimensional picture of customer risks can move the risk control port forward, achieve closed-loop risk management across the entire evaluation process, and empower commercial banks with more accurate marketing capabilities.