摘要
贝叶斯网络能够用条件概率较好地表达不确定性因果关系,并进行一定的推理.基于商业银行全面风险管理的复杂性,较难采用传统方法构建预警系统,采用贝叶斯网络,通过构建商业银行全面风险的拓扑结构,将各类风险诱因对商业银行全面风险的影响纳入到具有因果关联的网络结构中,测算了各类指标对全面风险的影响程度,并通过预警系统的灯号模型,直观地展示了风险因素对商业银行全面风险的影响,以便帮助商业银行及时采取措施化解风险.
Bayesian networks can oeseribe better the uncertainty by using conditional probability and ratiocination.Because of the coplexity of commercial bank＇s enterprise risk, it is difficult to build and ratiocination. Because of the complexity of commercial bank s enterprm pre-warning system by traditional methods. This paper uses the Bayesian networks as a new way to analyze the topology frame of enterprise risk and builds a causal network with key risk drives and enterprise risk, After evaluating every node, we calculate the effect of every risk factor on enterprise risk and vividly show the effect through the signal lamp model of pre-warning system, which can help commercial bank take action to deal with risks.
出处
《系统工程理论与实践》
EI
CSSCI
CSCD
北大核心
2012年第2期225-235,共11页
Systems Engineering-Theory & Practice
基金
国家社会科学基金(09BJL024)
重庆市自然科学基金(2009BB2042)
关键词
商业银行
全面风险管理
贝叶斯网络
预警
commercial banking
enterprise risk management
Bayesian networks
pre-warning
