A Massive Financial Risk Data Fusion Method Based on the Bayesian Network

Bayesian networks play an important role in financial risk data analysis, but there is a problem of low accuracy of risk prediction. Financial statistical analysis cannot solve the problem of accurate early warning in financial risks, and there are few early warnings. Therefore, this paper proposes a Bayesian network to construct. Firstly, the big data mining theory is used to grade the massive information, and the massive information is carried out according to the risk standards Set division to reduce ambiguity in early warning. Then, the big data mining theory grads the financial risk early warning forms a collection of early warning results and continuously warns the massive information. MATLAB simulation shows that under a certain amount of financial data, the Bayesian network’s early warning accuracy and warning time are superior to financial statistical analysis.