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Fraud detection is a knowledge-intensive activity. The main AI techniques used for fraud detection include: . Data mining to classify, cluster, and segment the data and automatically find associations and rules in the data that may signify interesting patterns, including those related to fraud.
Forensic accountants utilize an understanding of economic theories, business information, financial reporting systems, accounting and auditing standards and procedures, data management & electronic discovery, data analysis techniques for fraud detection, evidence gathering and investigative techniques, and litigation processes and procedures to ...
Benford's law has also been applied for forensic auditing and fraud detection on data from the 2003 California gubernatorial election, [43] the 2000 and 2004 United States presidential elections, [44] and the 2009 German federal election; [45] the Benford's Law Test was found to be "worth taking seriously as a statistical test for fraud ...
Forensic accountants need to have a great deal of access to information regarding the company they are investigating or assisting. The information will determine how much a person actually makes, the worth of a business, if there has been fraudulent activity, who committed the fraud, everyone involved, how much was taken from the company, where the money went, and how much can be recovered.
Forensic data analysis (FDA) is a branch of digital forensics. It examines structured data with regard to incidents of financial crime. The aim is to discover and analyse patterns of fraudulent activities. Data from application systems or from their underlying databases is referred to as structured data.
Sep. 30—MOSES LAKE — The Moses Lake School District is considering a forensic audit, after MLSD board member Paul Hill brought the idea up in closing comments of the Aug. 22 regular school ...
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