摘要
通过构建基于知识图谱的企业风险预测系统,探索知识图谱技术在商业银行风控领域的应用。利用内外部的结构化和非结构化数据,运用自然语言等技术挖掘企业上下游单位和密切关联个人,构建风险知识图谱,并建立风控关系挖掘模型。应用表明,通过构建企业风险垂直领域的客户关系知识图谱,帮助商业银行实现对客户及关联企业、人、事的全面高效监控,提前预知风险、减少损失。
Through the construction of enterprise risk prediction system based on knowledge graph, this paper explores the application of knowledge graph technology in the field of commercial bank risk management. Using internal and external structured and unstructured data, using NLP technology to mine upstream and downstream units and closely related individuals, build risk knowledge graph, and establish a risk management relationship mining model. The application shows that by building the knowledge graph of customer relationship in the vertical field of enterprise risk, commercial banks can achieve comprehensive and efficient monitoring of customers and related enterprises, people and things, predict risks in advance and reduce losses.
出处
《信息技术与标准化》
2019年第5期29-32,共4页
Information Technology & Standardization
关键词
知识图谱
人工智能
风险控制
knowledge graph
artificial intelletal
risk management
