Research and Implementation of Intelligent Financial Audit System Based on Deep Learning

With the increasing popularity of computer technology and network technology, database technology has been widely used in all walks of life. The intellectualization of audit work takes big data and artificial intelligence as the foundation and core, and adopts the form of audit template to fix the data acquisition technology, data sorting technology, data analysis technology, data mining technology and audit judgment technology with strong universality and high maturity, so as to form an audit software with audit template as the core. Traditional audit methods are difficult to find all kinds of financial problems hidden in massive data. According to the requirements of audit informatization and intelligent improvement, an intelligent audit framework is designed and a financial audit platform is developed based on data mining technology and deep learning algorithm. This paper expounds how to apply the innovative in-depth learning method to the audit process to solve the key problems in the project audit process, such as data collection and sorting, multi-source heterogeneous data feature extraction, project anomaly identification and project anomaly analysis. Based on the interdisciplinary thinking and the comprehensive use of data mining technology, fault diagnosis theory based on expert knowledge and financial audit theory, this paper develops an intelligent financial audit system which can deal with a variety of data types and automatically find audit clues.