摘要
金融行业对信贷风险管理要求渐高,传统风控方法难以满足小微企业需求。设计基于大数据的小微企业信贷风险预测与智能风控系统,利用大数据技术实现信贷风险精准预测与高效管理。系统整合数据采集、存储、模型预测与实时决策功能,运用随机森林、XGBoost和深度神经网络(Deep Neural Networks,DNN)等先进算法,提升风控决策准确性与实时性。经全面系统测试,验证其在API响应时间、数据处理速度和高并发响应能力等方面表现优异。该系统为小微企业信贷风险管理提供智能化方案,助力金融机构提高信贷审批效率与风控水平。
The requirements of the financial industry for credit risk management are gradually increasing,and traditional risk control methods are difficult to meet the needs of small and micro enterprises.A big data-based credit risk prediction and intelligent risk control system for small and micro enterprises is designed.With the help of big data technology,accurate prediction and efficient management of credit risks can be achieved.The system integrates data collection,storage,model prediction and real-time decision-making functions,and uses advanced algorithms such as Random Forest,XGBoost and deep neural networks(DNN)to improve the accuracy and real-time performance of risk control decisions.Through comprehensive system testing,its excellent performance in API response time,data processing speed and high-concurrency response ability has been verified.This system provides an intelligent solution for the credit risk management of small and micro enterprises,helping financial institutions improve credit approval efficiency and risk control levels.
作者
贾琼
JIA Qiong(Jiangsu Sushang Bank Co.,Ltd.,Nanjing Jiangsu 210019,China)
出处
《信息与电脑》
2025年第9期127-129,共3页
Information & Computer
关键词
大数据
小微企业
信贷风险预测
智能风控
big data
small and micro enterprises
credit risk prediction
intelligent risk control
