A review of money laundering literature: the state of research in key areas

M Tiwari, A Gepp, K Kumar - Pacific Accounting Review, 2020 - emerald.com
A review of money laundering literature: the state of research in key areas | Emerald Insight
Books and journals Case studies Expert Briefings Open Access Publish with us Advanced …

Regulatory technology (Reg-Tech) in financial stability supervision: Taxonomy, key methods, applications and future directions

X Chao, Q Ran, J Chen, T Li, Q Qian, D Ergu - International Review of …, 2022 - Elsevier
Financial regulation is the basic requirement for financial stability. Recently, regulatory
technology (Reg-Tech) has become one of the main research topics in financial stability …

Special issue on feature engineering editorial

T Verdonck, B Baesens, M Óskarsdóttir… - Machine learning, 2024 - Springer
In order to improve the performance of any machine learning model, it is important to focus
more on the data itself instead of continuously develo** new algorithms. This is exactly the …

Insurance fraud detection: Evidence from artificial intelligence and machine learning

F Aslam, AI Hunjra, Z Ftiti, W Louhichi… - Research in International …, 2022 - Elsevier
This study proposes a framework for fraud detection in the auto insurance industry by using
predictive models. The feature selection is performed utilizing a publicly available car …

CATCHM: A novel network-based credit card fraud detection method using node representation learning

R Van Belle, B Baesens, J De Weerdt - Decision Support Systems, 2023 - Elsevier
Advanced fraud detection systems leverage the digital traces from (credit-card) transactions
to detect fraudulent activity in future transactions. Recent research in fraud detection has …

Mathematical optimization in classification and regression trees

E Carrizosa, C Molero-Río, D Romero Morales - Top, 2021 - Springer
Classification and regression trees, as well as their variants, are off-the-shelf methods in
Machine Learning. In this paper, we review recent contributions within the Continuous …

Data engineering for fraud detection

B Baesens, S Höppner, T Verdonck - Decision Support Systems, 2021 - Elsevier
Financial institutions increasingly rely upon data-driven methods for develo** fraud
detection systems, which are able to automatically detect and block fraudulent transactions …

The value of big data for credit scoring: Enhancing financial inclusion using mobile phone data and social network analytics

M Óskarsdóttir, C Bravo, C Sarraute, J Vanthienen… - Applied Soft …, 2019 - Elsevier
Credit scoring is without a doubt one of the oldest applications of analytics. In recent years, a
multitude of sophisticated classification techniques have been developed to improve the …

[BOOK][B] Fraud analytics using descriptive, predictive, and social network techniques: a guide to data science for fraud detection

B Baesens, V Van Vlasselaer, W Verbeke - 2015 - books.google.com
Detect fraud earlier to mitigate loss and prevent cascading damage Fraud Analytics Using
Descriptive, Predictive, and Social Network Techniques is an authoritative guidebook for …

Artificial intelligence and fraud detection

Y Bao, G Hilary, B Ke - Innovative Technology at the Interface of Finance …, 2022 - Springer
Fraud exists in all walks of life and detecting and preventing fraud represents an important
research question relevant to many stakeholders in society. With the rise in big data and …