Forthcoming Articles

International Journal of Services Operations and Informatics

International Journal of Services Operations and Informatics (IJSOI)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Services Operations and Informatics (One paper in press)

Regular Issues

  • Anti Money Laundering Detection using Self-Improved Optimisation Approach with Graph Neural Network   Order a copy of this article
    by Shahrulniza Musa, Bhupendra Mishra 
    Abstract: Anti Money Laundering (AML) detection employs numerous approaches to identify and prevent money laundering. AML detection aims to prevent criminals from laundering money and financing illegal operations while guaranteeing regulatory compliance. Each level of ML detection is crucial to the AML system's success. To guarantee AML data accuracy, unprocessed information is cleaned, normalized, and standardised in pre-processing. Second, pre-processed data is used to extract key variables including transaction frequency, amount, location, account balance, and time. These qualities help detect suspicious transactions that need additional examination. Improved Principal Component Analysis extracts features. The third phase is graph creation, which uses chosen traits and their connections to identify money laundering. Finally, GNN-based optimization minimizes false positives and negatives by building a GNN model on the network to effectively detect and examine suspicious activity. GNN model accuracy and efficiency may be enhanced via self-improved Bald Eagle Optimisation (SI-BEO) by implementing in python platform.
    Keywords: Anti Money Laundering; GNN; I-PCA; Deep Learning; Self-Improved Bald Eagle Optimization.
    DOI: 10.1504/IJSOI.2026.10080234
     

 

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