Process science in action: A literature review on process mining in business management

P Zerbino, A Stefanini, D Aloini - Technological Forecasting and Social …, 2021 - Elsevier
Process Mining is a new kind of Business Analytics and has emerged as a powerful family of
Process Science techniques for analysing and improving business processes. Although …

Credit card fraud detection using a new hybrid machine learning architecture

EF Malik, KW Khaw, B Belaton, WP Wong, XY Chew - Mathematics, 2022 - mdpi.com
The negative effect of financial crimes on financial institutions has grown dramatically over
the years. To detect crimes such as credit card fraud, several single and hybrid machine …

The state-of-the-art of business process mining challenges

H R'bigui, C Cho - International Journal of Business Process …, 2017 - inderscienceonline.com
Business process mining is a new method that amalgamates business process modelling
and analysis with data mining and machine learning techniques, whereby knowledge from …

Anomaly detection in business processes using process mining and fuzzy association rule learning

R Sarno, F Sinaga, KR Sungkono - Journal of Big Data, 2020 - Springer
Much corporate organization nowadays implement enterprise resource planning (ERP) to
manage their business processes. Because the processes run continuously, ERP produces …

[HTML][HTML] Mining association rules for anomaly detection in dynamic process runtime behavior and explaining the root cause to users

K Böhmer, S Rinderle-Ma - Information Systems, 2020 - Elsevier
Detecting anomalies in process runtime behavior is crucial: they might reflect, on the one
side, security breaches and fraudulent behavior and on the other side desired deviations …

Application of machine learning and resampling techniques to credit card fraud detection

CL Udeze, IE Eteng, AE Ibor - Journal of the Nigerian Society of …, 2022 - journal.nsps.org.ng
The application of machine learning algorithms to the detection of fraudulent credit card
transactions is a challenging problem domain due to the high imbalance in the datasets and …

A semantic rule based digital fraud detection

M Ahmed, K Ansar, CB Muckley, A Khan… - PeerJ Computer …, 2021 - peerj.com
Digital fraud has immensely affected ordinary consumers and the finance industry. Our
dependence on internet banking has made digital fraud a substantial problem. Financial …

Deep reinforcement learning for data-efficient weakly supervised business process anomaly detection

EA Elaziz, R Fathalla, M Shaheen - Journal of Big Data, 2023 - Springer
The detection of anomalous behavior in business process data is a crucial task for
preventing failures that may jeopardize the performance of any organization. Supervised …

Towards explainable artificial intelligence in financial fraud detection: Using shapley additive explanations to explore feature importance

P Fukas, J Rebstadt, L Menzel, O Thomas - International Conference on …, 2022 - Springer
As the number of organizations and their complexity have increased, a tremendous amount
of manual effort has to be invested to detect financial fraud. Therefore, powerful machine …

[PDF][PDF] A survey on digital fraud risk control management by automatic case management system

W Haoxiang, S Smys - Journal of Electrical Engineering and …, 2021 - scholar.archive.org
In this digital era, a huge amount of money had been laundered via digital frauds, which
mainly occur in the timeframe of electronic payment transaction made by first-time …