Forensic accounting and Cybersecurity examine their interrelation in the detection and Prevention of financial fraud

Abstract

Due to the increase in the number of financial crimes and the increase in the number of cases related to this type of crimes in the courts, and because the task falls on the shoulders of a judicial accountant, the classical methods no longer work because of the complexity of cases and the increase in their number, and because the development of technology has contributed to the increase in the number of these crimes, also contributed with techniques through artificial intelligence in data analysis and easy access to solving these crimes, and this study aims to identify the effectiveness of machine learning in criminal accounting and its ability to facilitate the work of judicial accountants vıa Fraud detection is one of the main applications of artificial intelligence and machine learning in forensic accounting. By analyzing large data sets, machine learning algorithms can identify patterns and anomalies that may indicate fraudulent activity. These algorithms can also learn from previous cases and improve their accuracy over time ,Machine learning algorithms can identify irregularities and inconsistencies that may indicate financial crimes such as money laundering, embezzlement and tax fraud and is used in predictive analytics, allowing forensic accountants to anticipate possible financial crimes before they occur