Biometric authentication is gaining the interest of private, public, consumer electronics and
corporate security systems. For the protection of cyberspace from hackers and other harmful …

Financial fraud negatively impacts organizational administrative processes, particularly
affecting owners and/or investors seeking to maximize their profits. Addressing this issue …

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The ease with which mobile money is used to facilitate cross‐border payments presents a
global threat to law enforcement in the fight against money laundering and terrorist …

This study explores the fusion of artificial intelligence (AI) and machine learning (ML)
methods within anti–money laundering (AML) frameworks using data from the US Treasury's …

As the largest blockchain platform that supports smart contracts, Ethereum has developed
with an incredible speed. Yet due to the anonymity of blockchain, the popularity of Ethereum …

This paper aims to classify disciplinary hearings into two types (settlement and contested).
The objective is to employ binary machine learning classifier algorithms to predict the …

Purpose This study aims to describe and empirically explore a new method for bank anti-
money laundering (AML) systems using machine learning models. Current automated …

Introduction This study investigates the application of machine learning (ML) algorithms, a
subset of artificial intelligence (AI), to predict financial distress in companies. Given the …

This article used machine learning (ML) and artificial neural network (ANN) algorithms to
predict the likelihood of a country being sanctioned by the Basel Institute on Governance for …