Interactions between regulations, law, new technologies, and organizational policies in financial fraud detection – a case study of Serbia
Автор: Aleksandar Đorđević, Boris Jevtić, Stevica Deđanski
Журнал: Pravo - teorija i praksa @pravni-fakultet
Рубрика: Articles
Статья в выпуске: 4 vol.41, 2024 года.
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Digitization has led to the emergence of increasingly sophisticated forms of financial fraud, necessitating more advanced and integrated approaches for their rapid detection and prevention. This challenge prompted the authors to examine relevant literature and analyze current policies and measures for detecting financial fraud within the digital environments of organizations, with the aim of enhancing proactive prevention strategies. To this end, an online empirical survey was conducted with 118 executives and managers from Serbia during the first half of 2024, supported by the Association of Employers of Serbia and the Association of Managers. The research focused on the impact of new technologies, particularly AI, on the regulations and organizational policies related to financial fraud detection. Qualitative research, which utilized 12 predefined statements within each impact group using a five-point Likert scale, provided insights into the actual experiences and perspectives of participants concerning financial fraud as a distinct business, social, and economic issue. Multiple correlation approaches were employed to analyze the data. The outcomes suggest that all analyzed factors contribute to addressing financial fraud, with new technologies – especially those based on artificial intelligence – and corporate policies and strategies playing significant roles. Conversely, regulations have a lesser impact, attributed to their correctness, implementation, and enforcement. These findings enhance the understanding of the significance of taking a comprehensive approach to combating fraud, corruption, and financial crime, and highlight the roles of continuous technological advancements, employee digital education, and enhanced communication with the public and investors in building trust and maintaining a company’s reputation.
Digitization, legal framework, financial fraud, artificial intelligence, company policy
Короткий адрес: https://sciup.org/170206445
IDR: 170206445 | DOI: 10.5937/ptp2404048D
Список литературы Interactions between regulations, law, new technologies, and organizational policies in financial fraud detection – a case study of Serbia
- Ahmed, M., Mahmood, A. N., & Islam, M. R. (2016). A survey of anomaly detection techniques in finan-cial domain. Future Generation Computer Systems, 55, pp. 278–288. https:// doi.org/10.1007/978-3-030-70713-2_60.
- Abdallah, A., Maarof, M. A., & Zainal, A. (2016). Fraud detecton system: A survey. Journal of Network and Computer Applications, 68, pp. 90–113. https://doi.org/10.3390/app12199637
- Akindote, O. J., Adegbite, A. O., Dawodu, S. O., Omotosho, A., Anyanwu, A., & Maduka, C. P. (2023). Comparative review of big data analytics and GIS in healthcare decision-making. World Journal of Ad-vanced Research and Reviews, 20(3), pp. 1293–1302 http://dx.doi.org/10.30574/wjarr.2023.20.3.2589
- Apostolou, B., & Apostolou, N. (2012). The value of risk assessment: Evidence from recent surveys. The Forensic Examiner, 21(3), Downloaded 2024, August 31 from http://www.theforensicexaminer.com/
- Blanke, J.M. (2020). Protection for ‘Inferences drawn’: A comparison between the general data protec-tion regulation and the California consumer privacy act. Global Privacy Law Review, 1(2). http://dx.doi. org/10.54648/gplr2020080
- Crockford, G. N. (2005). The changing face of risk management, Geneva Papers on Risk & Insurance – Issues & Practice, 30(1), pp. 5–10. http://dx.doi.org/10.1057/palgrave.gpp.2510019
- Dai, Y., & Handley-Schachler, M. (2015). A fundamental weakness in auditing: The need for a conspiracy theory. Procedia Economics and Finance, 28, pp. 1–6. DOI: 10.1016/S2212-5671(15)01074-6.
- Deđanski, S., & Jevtić, B. (2024). Uticaj veštačkom inteligencijom podržanih usluga na korisničko is-kustvo – primer hotelske industrije Srbije [The impact of artificial intelligence-supported services on user experience – the example of the Serbian hotel industry], Limes-plus, 1-2, in press
- Ha, N., Xu, K., Ren, G., Mitchell, A. & Ou, J.Z. (2020). Machine learning‐enabled smart sensor systems. Advanced Intelligent Systems, 2(9), pp. 2000063. http://dx.doi.org/10.1002/aisy.202000063
- Jevtić, B., Deđanski, S., Beslać, M., Grozdanić, R., & Damnjanović, A. (2013). SME Technology Capacity Building for Competitiveness and Export – Evidence from Balkan Countries, Metalurgija International, 18(spec.iss.4), pp. 162–170
- Jevtić, B., Beslać, M., Janjušić, D., & Jevtić M. (2024). The effects of digital natives’ expectations of tech hotel services quality on customer satisfaction, International Journal for Quality Research, 18(1), pp. 1–10. DOI: 10.24874/IJQR18.01-01
- Lewis-Beck, M. S., Bryman, A. & Futing Liao, T. (2004). The SAGE encyclopedia of social science re-search methods, SAGE Publications Ltd. DOI: 10.4135/9781412950589.
- Lister, L. M. (2007). A practical approach to fraud risk. Internal Auditor, 64(6), pp. 61–65. Downloaded 2022, January 21 from https://na.theiia.org/Pages/IIAHome.aspx
- Maynard, G. R. (1999). Embracing risk. Internal Auditor, 56(1), pp. 24–29. Downloaded 2022, March 21 from https://na.theiia.org/Pages/ IIAHome.aspx
- Mehr, R. I., & Forbes, S. W. (1973). The risk management decision in the total business setting. Journal of Risk & Insurance, 40(3), pp. 389–401. http://dx.doi.org/10.2307/252226
- Miškić, M., Srebro, B., Rašković, M., Vrbanac, M., & Jevtić, B. (2024). Key Challenges Hindering SMEs’ full benefit from Digitalization – A Case Study from Serbia, International Journal for Quality Research, 19(2). DOI: 10.22874/IJQR1902-03.
- Naqshbandi, K. M. A. (2017). Towards understanding corporate social responsibility. Pakistan & Gulf Economist. Downloaded 2024, April 15 from http://www.pakistaneconomist.com
- Rockness, H., & Rockness, J. (2005). Legislated ethics: From Enron to Sarbanes-Oxley, the impact on corporate America. Journal of Business Ethics, 57(1), pp. 31–54. DOI: 10.1007/s10551-004-3819-0
- Sengur, E. D. (2012). Auditors’ perception of fraud prevention measures: Evidence from Turkey. An-nales Universitatis Apulensis – Series Oeconomica, 14(1), pp. 128. http://dx.doi.org/10.29302/oeconomica.2012.14.1.11
- Snider, H. W. (1991). Risk management: A retrospective view. Risk Management (00355593), 38(4), pp. 47–54. Downloaded 2024, April 10 from http://www.rmmag.com/
- Servaes, H., Tamayo, A., & Tufano, P. (2009). The theory and practice of corporate risk management. Journal of Applied Corporate Finance, 21(4), pp. 60–78. DOI:10.1111/j.1745-6622.2009.00250.x
- Srivastava, R. P., Mock, T. J., & Gao, L. (2011). The DempsterShafer theory: An introduction and fraud risk assessment illustration. Australian Accounting Review, 21(3), pp. 282–291. DOI:10.1111/j.1835-2561.2011.00135.x
- Stake, R. E. (2006). Multiple case study analysis. New York: The Guilford Press.
- Srebro, B., Paunović, L., & Jevtić, B. (2024). Unraveling Hospitality: Exploring Human, Digital, and Ex-ternal Forces in Marketing Communications. In: XIX International symposium SymOrg, Zlatibor (pp. 617–625). Belgrade: University of Belgrade, Faculty of Organizational Sciences
- Špiler, M., Milošević, D., Miškić, M., Gostimirović, L., Beslać, M., & Jevtić, B. (2023). Investments in dig-ital technology advances in textiles, Industria Textila, 74(1), pp. 90–97, DOI: 10.35530/IT.074.01.202287