Audit risks and prevention strategies of corporate accounting based on computer technology

Abstract

Business owners use professional auditors to do audits on their companies because auditors are essential partners in the growth of enterprises. Auditors may improve their ability to organize their audit work sensibly and provide accurate audit opinions if they effectively identify the risks associated with the audit. In this day and age of big data and the World Wide Web, businesses produce a significant quantity of data through the normal course of their activities. Using data mining techniques, deep learning, neural networks, and other developing technologies to extract excellent auditing data from the massive amounts of data produced by audited businesses is a significant challenge for auditors. As a result, the purpose of this research is to use computer data mining methods in order to develop an audit risk model. This model will give an example for auditors to use when doing big data analysis and will mine important data, which will ultimately result in an improvement in the audit process's efficiency as well as its correctness.