Using Bayesian belief networks to evaluate credit guarantee-risk

The evaluation of credit, guarantee risk (herein after called CGR) involves many complex problems such as how to quantify risk, how to express causal relationships of risk factors, how to fuse all kinds of information and evaluate risk with uncertainties. So the evaluation of CGR is very difficult because of its uncertainty and diverse information. Bayesian belief networks (herein after called BBN) are basically a framework for reasoning uncertainty and diverse information. This paper presents BBN as a new methodology to evaluate CGR. An example is presented by this method.