The paper contributes to a growing body of empirical work on regulatory technology by
proposing machine learning models to detect fraud in financial markets. The recent spate of …

Fraud not only damages the wealth and reputation of individuals, but also poses a threat to
social security. Although the relationship between financial literacy and resident fraud …

This paper aims to build a machine learning and a neural network model to detect the
probability of money laundering in banks. The paper's data came from a simulation of actual …

Abstract The Tinder Swindler is a Netflix documentary that documents the stories of three
women who were swindled of their life savings by a man, Simon Leviev (" Leviev"), who …

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 …

Investment fraud continues to be a severe problem in the Canadian securities industry. This
paper aims to employ machine learning algorithms and artificial neural networks (ANN) to …

Purpose The ongoing evolution of the Internet and the subsequent digitalisation of financial
services, along with the ever-increasing innovation of financial products, have rendered …

As businesses undergo digital transformation, supply chain fraud poses an increasing
threat, necessitating more sophisticated detection and prevention methods. This paper …

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 …

In today's technologically advanced world, the escalating prevalence of phishing attacks
necessitates an urgent exploration of effective countermeasures. This study delves into the …