基于数据挖掘技术的财务会计欺诈检测综述

The detection of financial accounting fraud is crucial in modern enterprise management. With the rapid development of data mining techniques, an increasing number of studies have begun to apply these methods to identify and prevent fraudulent activities. By analyzing large volumes of financial data, data mining techniques can uncover potential anomalies and trends, aiding businesses in timely fraud risk identification. Various data mining methods, such as classification, clustering, and anomaly detection, have been widely utilized in financial fraud detection. Research indicates that these techniques not only enhance detection accuracy but also reduce the costs associated with manual audits. Furthermore, with advancements in machine learning and artificial intelligence, the future of financial fraud detection is poised to become more intelligent and automated. Overall, the application of data mining techniques in financial accounting fraud detection holds significant promise and warrants further research and exploration.