机构地区: 广东科技学院
出 处: 《南昌大学学报(工科版)》 2012年第2期188-192,196,共6页
摘 要: 由于传统担保系统存在无法实现风险控制和客户保留等智能化功能的缺陷,导致担保公司贷款风险增加且审批周期过长、客户流失严重等问题。为解决上述问题,提出基于粗集神经网络模型来解决担保企业的风险控制方法;用层次分析法(AHP)和基础分类活动(ABC)模型来实现客户分群,从而有效地解决客户流失等问题;对深圳担保协会提供的2001—2011年的企业样本数据进行仿真。实验结果表明:相对传统的担保系统而言,基于商务智能的担保系统具有风险控制准确率高、审批效率高、客户分群合理等优点,所提出的模型可为智能化担保系统设计提供一种新选择。 As lack of intelligence, traditional guarantee has drawbacks of too high load risk, too long approval time and causing customer drain. To solve these issues,the article put forward a new kind of neural network model based on rough set,and used analytic hierarchy process (AHP) and activity based classification (ABC) to realize customer grouping; then simulation test was done with company sample data. The results showed that guarantee sys- tem of intelligence could offer more accurate risk control, more short approval time and more rational customer grouping. So the model would be a new and good selection for intelligence guarantee system design.
领 域: [自动化与计算机技术] [自动化与计算机技术]