Abstract: Different data mining methods for classification can produce different results. However, "one time" data mining process cannot often obtain a well support decision, so we introduce information fusion technique to fuse the different results to gain an optimal solution. In this paper, information fusion technique is used to build a finance early-warning model based on data mining methods such as SVM and Logistic model, which can integrate the respective strengths from different data mining methods to improve the prediction accuracy rate, it fuses the different data mining results to gain the prediction results for reliable decision. The real dataset of Chinese listed manufacturing companies is selected to predict the finance risk with information fusion technique based on SVM and Logistic model, and a higher prediction accuracy than those of the two methods respectively is obtained.

Key words: finance early-warning, SVM model, logistic model, information fusion