Detecting Cyber Fraud in Banking Transactions via Machine Learning Techniques: Implications for Financial Stability

This study empirically investigates the performance of Elastic Machine Learning, an industrial, unsupervised anomaly detection tool, in the identification of fraudulent behavior in banking transactions. Using AI-generated datasets that were designed to simulate realistic banking environments, the an...

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Bibliografische Detailangaben

Hauptverfasser:	Lamprini Konsta, Dimitrios Dimitriou, Anastasios Papathanasiou, Vasiliki Liagkou
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	MDPI AG 2026-03-01
Schriftenreihe:	FinTech
Schlagworte:	cybercrime machine learning elastic software banking sector financial system
Online-Zugang:	https://www.mdpi.com/2674-1032/5/1/23
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