Volume 23, Issue 3 (9-2026)                   jor 2026, 23(3): 0-0 | Back to browse issues page

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Faridi Masouleh M, Yousefi Kenarsari M. Financial Fraud Detection Using Artificial Intelligence Tools. jor 2026; 23 (3)
URL: http://jamlu.lahijan.iau.ir/article-1-2299-en.html
Financial Fraud Detection Using Artificial Intelligence Tools
M. Faridi Masouleh * , M. Yousefi Kenarsari
Ahrar Institute of Higher Education, Rasht, Iran , m.faridi@ahrar.ac.ir
Abstract:   (66 Views)
Recent years have witnessed a significant surge in the volume of electronic financial transactions, consequently elevating the risk of fraudulent activities. Traditional methods for detecting such fraud are often laborious and time-intensive, underscoring the growing importance of leveraging artificial intelligence (AI) algorithms for financial transaction fraud detection. This research introduces a novel model employing Convolutional Neural Networks (CNN) specifically designed for identifying fraudulent financial transactions. The dataset comprises authentic financial transactions, meticulously optimized through advanced pre-processing and machine learning techniques. Experimental outcomes demonstrate that the proposed methodology achieves a high degree of accuracy in fraud detection, significantly outperforming conventional approaches. This study concludes that the integration of AI holds substantial promise for effectively mitigating financial losses stemming from fraudulent transactions.
 
Keywords: Fraud Detection, Artificial Intelligence (AI), Convolutional Neural Network (CNN), Financial Transaction.
     
Type of Study: Applicable | Subject: Special
Received: 2026/04/4 | Accepted: 2026/09/1 | Published: 2026/09/11
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