Research on University Intelligent Financial Audit System Based on Data Mining

Abstract

The traditional university financial management model has problems such as low efficiency and high cost, which cannot meet the requirements of the development trend of the current era. Major universities are exploring the reform of financial management model one after another. At present, the budgeting of colleges and universities in our country is still at a low level, and the budgeting is not detailed enough. Moreover, there is no corresponding monitoring and early warning mechanism in budget implementation, resulting in poor budget execution. In order to realize the classification and management of audit issues, this paper uses NLP, artificial intelligence, data mining technology, and financial audit theory with a cross-disciplinary thinking, and proposes a feature fusion short text classification algorithm based on BiLSTM neural network, and examines the effectiveness of the algorithm. Experimental verification. The experiment verifies the effectiveness of the feature fusion short text classification algorithm based on BiLSTM neural network, and proves the effectiveness of the intelligent financial audit system designed in this paper.