Considering that with the rapid expansion of electronic data, the traditional audit approachs can not cope with vast business data, this paper intend to introduce the Clustering and Association Rule Mining in the audit fields. Based on the study of the meaning of Clustering and Association Rule Mining and their Algorithm—K-Means and Apriori, this article proposed an audit model which is based on the Clustering and Association Rule Mining, at the same time, taking the audit of medical insurance of some a city as an example, it detailed first how to use the Clustering to filter data, then how to mining the potential relationships in vast data so as to determine the audit priorities and audit clues.Through the case, the article is committed to provide a reference for the application of data mining in the fraud information identification.