Dynamic Bayesian Network Model for the Enterprise Financial Risk Warning

At present, the methods of enterprise financial risk warning emphasize static function dependency or dynamic propagation of time series, which results in a unconsistent combination of the static and dynamic information. In this paper, a dynamic hierarchical naive Bayesian network model is developed for enterprise financial risk warning. The process of using the model and the methods of analyzing contribution on risk level prediction are presented. This model features universality and can be widely used in other risk warning domains.