Investigating Innovative Approaches to Identify Financial Fraud in Real-Time

Tanvir Rahman, Akash and Md Sultanul Arefin, Sourav and Md Shakil, Islam (2024) Investigating Innovative Approaches to Identify Financial Fraud in Real-Time. American Journal of Economics and Business Management, 7 (11). pp. 1262-1265. ISSN 2576-5973

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Abstract

Financial fraud poses a significant threat to global economies, costing businesses and individuals billions annually. With the rise of digital transactions, traditional methods of fraud detection are no longer sufficient. This paper explores cutting-edge approaches to real-time financial fraud detection, including artificial intelligence (AI), machine learning (ML), blockchain technology, and behavioral analytics. Through an in-depth analysis of their capabilities and limitations, we highlight how these approaches enable organizations to mitigate fraud risks effectively while maintaining operational efficiency. We also provide data-driven insights into detection rates, cost efficiency, and industry-specific challenges, supported by extensive case studies and real-world applications.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Postgraduate > Master's of Islamic Education
Depositing User:	Journal Editor
Date Deposited:	01 Jan 2025 05:33
Last Modified:	01 Jan 2025 05:33
URI:	http://eprints.umsida.ac.id/id/eprint/15048

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