Deep learning and explainable artificial intelligence techniques applied for detecting money laundering–a critical review

DV Kute, B Pradhan, N Shukla, A Alamri - IEEE access, 2021 - ieeexplore.ieee.org
Money laundering has been a global issue for decades, which is one of the major threat for
economy and society. Government, regulatory and financial institutions are combating it …

Money Laundering: A Bibliometric Review of Three Decades from 1990 to 2021

D Ahuja, P Bhardwaj, P Madan - Smart Analytics, Artificial Intelligence …, 2023 - emerald.com
Purpose: This study aims to employ bibliometric analysis to condense multiple studies into a
single publication that not only gives insights into the growth and advancement of the …

[HTML][HTML] Predicting fraud in financial payment services through optimized hyper-parameter-tuned XGBoost model

S Dalal, B Seth, M Radulescu, C Secara, C Tolea - Mathematics, 2022 - mdpi.com
Online transactions, medical services, financial transactions, and banking all have their
share of fraudulent activity. The annual revenue generated by fraud exceeds $1 trillion. Even …

Artificial intelligence in accounting and finance: Challenges and opportunities

Z Yi, X Cao, Z Chen, S Li - IEEE Access, 2023 - ieeexplore.ieee.org
The rapid expansion of artificial intelligence (AI) technologies presents novel technical
solutions to traditional accounting and finance problems. Despite this, scholars in …

[HTML][HTML] Factors influencing the choice of technique to launder funds: The APPT framework

M Tiwari, J Ferrill, A Gepp, K Kumar - Journal of Economic Criminology, 2023 - Elsevier
This paper proposes a new framework to provide insights into the techniques launderers
adopt to clean illicit funds, drawing on existing literature and theories including rational …

Anti-money laundering by group-aware deep graph learning

D Cheng, Y Ye, S Xiang, Z Ma… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Anti-money laundering (AML) is a classical data mining problem in finance applications. As
well known, money laundering (ML) is critical to the effective operation of transnational and …

Dark web data classification using neural network

AS Rajawat, P Bedi, SB Goyal, S Kautish… - Computational …, 2022 - Wiley Online Library
There are several issues associated with Dark Web Structural Patterns mining (including
many redundant and irrelevant information), which increases the numerous types of …

Incorporating machine learning and a risk-based strategy in an anti-money laundering multiagent system

CR Alexandre, J Balsa - Expert Systems with Applications, 2023 - Elsevier
Over the last decade, the international community has become more aware of the danger
and harm caused by the practice of the crime of Money Laundering (ML). Organizations to …

Towards Understanding Asset Flows in Crypto Money Laundering Through the Lenses of Ethereum Heists

J Wu, D Lin, Q Fu, S Yang, T Chen… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With the overall momentum of the blockchain industry, financial crimes related to blockchain
crypto-assets are becoming increasingly prevalent. After committing a crime, the main goal …

Mobile money fraud detection using data analysis and visualization techniques

R Al-Sayyed, E Alhenawi, H Alazzam, A Wrikat… - Multimedia Tools and …, 2024 - Springer
Financial investigations in the realm of fraud detection demand rigorous data analysis to
identify anomalies and inform decision-making. This paper demonstrates the importance of …