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- Title
Financial Statement Fraud Detection in the Digital Age.
- Authors
Kasztelnik, Karina; Jermakowicz, Eva K.
- Abstract
This article explores the use of artificial intelligence (AI) and technology tools in detecting and preventing financial statement fraud. It acknowledges the prevalence of fraud in financial statements and the need for innovative controls and processes to mitigate these risks. The article explains how AI, machine learning, and natural language processing can be utilized to analyze large amounts of data, identify patterns and anomalies, and uncover potential fraudulent activities. It emphasizes the importance of human involvement and expertise in training AI models and interpreting the results. The article also discusses data mining techniques, such as classification, clustering, prediction, regression, visualization, and anomaly detection, and their applications in detecting financial statement fraud. It highlights the use of robotic process automation (RPA) and predictive analytics in fraud detection, comparing them to traditional methodologies and addressing the associated risks. The article stresses the need for careful planning, investment in resources and expertise, and a commitment to data quality, privacy, and security when implementing these technologies.
- Subjects
FINANCIAL statements; DIGITAL technology; FRAUD investigation; AUDITING standards; INTERNAL auditing; ARTIFICIAL intelligence; NATURAL language processing; STATISTICAL learning
- Publication
CPA Journal, 2024, Vol 94, Issue 3/4, p32
- ISSN
0732-8435
- Publication type
Article