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Bankrobotics: Artificial Intelligence and Machine Learning Powered Banking Risk Management — Prevention of Money Laundering and Terrorist Financing

Author

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  • Prisznyák, Alexandra

Abstract

Based on a country study related to money laundering and terrorist financing, the Financial Action Group downgraded Hungary’s compliance with Recommendation R15 (use of new technologies). At the same time, between 2020 and 2021, the Magyar Nemzeti Bank imposed fines on several commercial banks operating in Hungary for shortcomings on complying with money laundering and terrorist financing regulations. As a gap-filling analysis, the study examines supervised (classification, regression), unsupervised (clustering, anomaly detection), and hybrid machine learning models and algorithms operating based on highly unbalanced dataset of anti-money laundering and terrorist financing prevention of banking risk management. The author emphasizes that there is no one ideal algorithm. The choice between machine learning algorithm is highly determined based on the underlying theoretical logic and additional comparative. Model building requires a hybrid perspective of the give business unit, IT and visionary management.

Suggested Citation

  • Prisznyák, Alexandra, 2022. "Bankrobotics: Artificial Intelligence and Machine Learning Powered Banking Risk Management — Prevention of Money Laundering and Terrorist Financing," Public Finance Quarterly, Corvinus University of Budapest, vol. 67(2), pages 288-303.
  • Handle: RePEc:pfq:journl:v:67:y:2022:i:2:p:288-303
    DOI: https://doi.org/10.35551/PFQ_2022_2_8
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    More about this item

    Keywords

    Artificial Intelligence; Machine Learning algorithms; banking risk management; AntiMoney Laundering and Counter Financing Terrorism; supervised/unsupervised methods;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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