Exploring detection and prevention of money laundering with information technology

Abstract

Purpose

Regarding the magnitude of the impact caused by money laundering, the size of the organization and the many parties involved, this paper aims to explore the methods used in detecting money laundering, especially the use of technology.

Design/methodology/approach

This research is a literature review from various research sources originating from Pro-Quest, Emerald, Science Direct and Google Scholar.

Findings

The researchers found that the most widely used methods for detecting money laundering were artificial intelligence, machine learning, data mining and social network analysis.

Research limitations/implications

This research is expected to help the government or institutions such as the police, forensic accountants and investigative auditors in the fight against money laundering. This research is limited to only a few sources, and it is hoped that further research can explore more deeply related to other methods for detecting money laundering.

Originality/value

This paper discusses the methods that are widely used in detecting money laundering.