Pioneering AI-Driven Fraud Detection and AML Strategies: Transforming Azerbaijan's Banking Landscape through Innovative Machine Learning Algorithms and Behavioral Analytics

Ramin, Abbasov (2024) Pioneering AI-Driven Fraud Detection and AML Strategies: Transforming Azerbaijan's Banking Landscape through Innovative Machine Learning Algorithms and Behavioral Analytics. American Journal of Economics and Business Management, 7 (4). pp. 31-36. ISSN 2576-5973

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Abstract

The essay aims to examine how AI-based strategies for fraud detection and AML in Azerbaijan’s banking establishments are potentially capable of playing a transformational role. It explores the fact that fraud and anti-money laundering (AML) are current issues and, hence, provides the reader with novel machine learning algorithms and behavior analytics built by the author. Research shows that these methods are good at discerning fraud and identifying people who are sly. The paper also covers the matter of implementation barriers and presents ideas for successful implementation, creating a better way for more secure and effective banks in the Azerbaijani context.

Item Type:	Article
Subjects:	H Social Sciences > HG Finance
Divisions:	Postgraduate > Master's of Islamic Education
Depositing User:	Journal Editor
Date Deposited:	22 Apr 2024 04:45
Last Modified:	22 Apr 2024 04:45
URI:	http://eprints.umsida.ac.id/id/eprint/13653

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