Keywords
money
terrorism financing
How to Cite
Abstract
The study aimed to understand the impact of artificial intelligence on the effectiveness of measures to prevent money laundering and terrorist financing in the financial sector. Research problems focused on identifying areas where AI can effectively improve preventive actions and on understanding the challenges associated with implementing this technology in the context of financial security. The aim of the work included an analysis of the prospects for the development of AI in activities to prevent money laundering and terrorism financing and an assessment of its impact on the effectiveness of preventive activities. The research hypothesis assumed that developed AI systems could increase the effectiveness of detecting illegal transactions and terrorist activities. The conclusions indicate that the development of AI is crucial for the effective fight against financial crime, but at the same time requires constant adaptation to the evolving threat environment. The message of the study suggests that investments in the development of AI in the financial sector are necessary to maintain security and effectively prevent financial crime.
References
Anderson, M., Anderson, L. S. (2007). Machine Ethics: Creating an Ethical Intelligent Agent. AI Magazine, No. 28(4)
Brynjolfsson, E., Mcafee, A. (2015). Drugi wiek maszyn. Praca, postęp i dobrobyt w czasach genialnych technologii, MT Biznes, Warszawa/
Dalvinder, S. G. (2014). A Critical Conceptual Analysis of Definitions of Artificial Intelligence as Applicable to Computer Engineering, IOSR Journal of Computer Engineering, No. 16(2).
Dignum, V. (2019). Responsible Artificial Intelligence. How to develop and use AI in a responsible way. Springer. Dubber.
Dubber M. D., Pasquale, F., Das, S. (2020). The Oxford Handbook of Ethics of AI. Oxford University Press, Oxford.
Gadre-Patwardhan, S., Katdare, V.V., Joshi, M.R. (2016). A Review of Artificially Intelligent Applications in the Financial Domain, eds. C. Dunis, P.
Middleton, A. Karathanasopolous, K. Theofilatos, Artificial Inteligencie in Financial Markets. New Developments in Quantitative Trading and Investment, Palgrave Macmillan, London.
Gao, Z. and Ye, M. (2007) A Framework for Data Mining-Based Anti-Money Laundering Research. Journal of Money Laundering Control, No. 10.
Hagendorff, T. (2020). The Ethics of AI Ethics: An Evaluation of Guidelines. Minds and Machines, No. 30.
Hanafi, A. (2010) The Dynamic Aspects of Criminal Act and Criminal Liability in Money Laundering Practices, Jurnal Hukum Ius Quia Iustum, No. 17.
Hendriyetty, N. and Grewal, B.S. (2017) Macroeconomics of Money Laundering: Effects and Measurements, Journal of Financial Crime, No. 24.
Hetemi, A., Merovci, S. and Gulhan, O. (2018) Consequences of Money Laundering on Economic Growth—The Case of Kosovo and Its Trade Partners.
Acta Universitatis Danubius, No. 14.
Huang, M.H. and Rust, R.T. (2018) Artificial Intelligence in Service. Journal of Service Research, No. 21.
Płoszajski, P. (2016). Czy nadszedł zmierzch monopolu człowieka na inteligencję? O maszynach myślących jak ludzie i ludziach myślących jak maszyny, Oficyna Wydawnicza SGH, Warszawa.
Płoszajski, P. (2016). Społeczna odpowiedzialność technologii, Oficyna Wydawnicza SGH, Warszawa.
Rojszczak, M. (2020). Sztuczna inteligencja w innowacjach finansowych – aspekty prawne i regulacyjne, Internetowy Kwartalnik Antymonopolowy i Regulacyjny, No. 2(9).
Sastry, V. V. L. N. (2019). Artificial Intelligence in Financial Services and Banking Industry, Blue Diamond Publishing, Shabbir.
Stylec-Szromek, P. (2018). Sztuczna inteligencja – prawo, odpowiedzialność, etyka, Organizacja i Zarządzanie, No. 123.
Teichmann, F.M. and Falker, M.C. (2020) Money Laundering through Consulting Companies. Journal of Financial Regulation and Compliance, No. 28
Turing, A.M. (2009). Computing Machinery and Intelligence, eds. Computer, R. Epstein, G. Roberts, G. Beber, Parsing the Turing Test. Philosophical and Methodological Issues in the Quest for the Thinking, Springe, Dordrecht.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright (c) 2024 Katarzyna Cyrkun, Karolina Nastaj-Sałek, Robert Sito, Henryk Noga, Wojciech Jakubiec