Assessment of Employees’ Perceptions on Anti-Money Laundering (AML) Practices and Correlation with Organisational Cybersecurity Maturity
Abstract
The purpose of this study was to assess employees’ perceptions of anti-money laundering practices at the National Development Bank in Botswana. The study used a quantitative approach. A sample of 84 respondents who are employees of the National Development Bank (NDB) of Botswana took part in the study. These were selected through a stratified random sampling method to ensure representation in all strata. A self-administered questionnaire was used to collect data. The study found out that employees of National Development Bank understand the concept of money laundering and the stages involved in money laundering. Secondly, the study established that the main causes of money laundering were corruption, politicians and prominent persons influence, and weak banking and financial systems. Thirdly, the study established that money laundering is harmful to the economy in different ways that include increased national crime, increased corruption, and negative effects on the economy. The study recommended that the management of NDB should adopt anti-money laundering/ combating/ counter terrorism financing (AML/CFT) regulations laid out by regulating bodies including those of the Financial Action Task Force (FATF), Bank of Botswana and the Financial Intelligence Agency (FIA). In addition to this, the bank management should expose its employee to continuous knowledge on ML/FT through in-house training and external workshops with other industry stakeholders. The bank should also adopt a robust record management system that is able to capture all transactions taking place within it. The system should be robust enough to flag suspicious ML/FT activities taking place through transactions carried out within the bank.
Downloads
Metrics
References
2. Anichebe, U. (2020). Combating money laundering in the age of technology and innovation. Social Science Research Network, 12, 1-35.
3. Arner, D. W. & Janosa, B. (2015). Fintech in China from the shadow. Journal of Financial Perspectives, 3, 78-91.
4. Arner, D. W., Dirk, A. Z., Ross, B. & Janos, B. (2019). The Identity Challenge in Finance: From Analogue Identity to Digitized Identification to Digital KYC Utilities. European Business Organisation Law Review, 20, 55-80.
5. Cassara, J. A. (2015). Trade-based money laundering: the next frontier in international money laundering enforcement. New York: Wiley.
6. Crowe, M. & Sheppard, L. (2010). Qualitative and quantitative research designs are more similar than different. Internet Journal of Allied Health Services and Practice, 4 (8), 1-6.
7. Dixon, H., (2017). Maintaining Individual Liability in AML and Cybersecurity at New York's Financial Institutions. Penn State Journal of Law and International Affairs, 5(1), 1-40.
8. Gara, M., & Pauselli, C. (2015). Looking at ‘Crying wolf’ from a different perspective: An attempt at detecting banks under- and over-reporting suspicious transactions. Banca d’Italia - Quaderni Dell’antiriciclaggio, 4, 1–26.
9. Gliem, J.A. and Gliem, R.R. (2003). Calculating, Interpreting, and Reporting Cronbach’s Alpha Reliability Coefficient for Likert-Type Scales. 2003 Midwest Research to Practice Conference in Adult, Continuing, and Community Education, pp.1-7
10. Gorsiga, M., Steg, L., Denkers, A. & Huisman, W. (2018). Corruption in organizations: ethical climate and individual motives. Administrative Sciences, 8(4), 1-19.
11. Henry, L. & Moses, S. (2020). An analysis of money laundering and Economic growth in Trinidad and Tobago. San Fernando: UWI Press.
12. Hetemi, A., Merovci, S. & Gulhan, O. (2018). Consequences of money laundering on economic growth. The case of Kosovo and its trade partners. Acta Universitatis Danubius OEconomica, 14(3), 113-125.
13. Kavanagh, C. (2013). Getting smart shaping up: Responding to the impact of drug trafficking in developing countries. A case study of Mozambique. Washington, DC: NYU Center on International Cooperation.
14. Lannegren, O. and Ito, H. (2017). The End of the ANC Era: An analysis of corruption and inequality in South Africa. Journal of Politics and Law, 10(4), 55-59.
15. Levi, M. & Gilmore, B. (2002). Terrorist finance, money laundering and the rise and rise of mutual evaluation: A new paradigm for crime control? European Journal of Law Reform, 4(2), 337-364.
16. Levi, M. (2010). Corruption and money laundering. Journal of Financial Crime, 17(1), 168-169.
17. Makochekwane, A. (2014). Is corruption really harmful to growth? Evidence from Zimbabwean. University of Zimbabwe Business Review, 2 (2), 1-17.
18. Maruatona, O (2013). Internet Banking Fraud Detection Using Prudent Analysis. Federation University
19. Maruatona, O., Vamplew, P., Dazeley, R., Watters, P. (2017). Evaluating accuracy in prudence analysis for cyber security. ICONIP 2017.
20. Teichmann, F.M.J. (2017). Twelve methods of money laundering. Journal of Money Laundering Control, 20(2), 130-137.
21. Motshegwa, B., Mutonono, P. & Mikhazu, T. (2019). Embezzlement of the National Petroleum Fund in Botswana. A paper presented at the 4th Annual International Conference on Public Administration and Development Alternatives 03-05 July 2019, Southern Sun Hotel, OR Tambo International Airport, Johannesburg, South Africa.
22. National Development Bank (NDB) (2020). Annual Prospectus. Gaborone: NDB.
23. O’Neill, M. (2014). The Internet of Things: do more devices mean more risks? Computer Fraud & Security, 14(1), 16-17.
24. Oke, T. (2016). Money laundering regulation and the African PEP: case for tougher civil remedy options. Journal of Money Laundering Control, 19(1), 32-57.
25. Osakede, K. (2015). Corruption in the Nigeria public sector: an impediment to good governance and sustainable development. Review of Public Administration and Management, 4 (8), 76-87.
26. Rahi, S. (2017). Research design and methods: A systematic review of research paradigms, sampling issues and instruments development. International Journal of Economic Management Science, 6(2), 1-5.
27. Rizzolli, M., & Saraceno, M. (2013). Better that ten guilty persons escape: Punishment costs explain the standard of evidence. Public Choice, 155(3), 395–411.
28. Root, V. (2019). The compliance process. Indiana Law Journal, 94 (1), 203-251.
29. Saunders, M., Lewis, P. & Thornhill, A. (2009). Research methods for business students. (5th Ed). Essex, England: Pearson Education Limited.
30. Sotelino, F. & Finel-Honigman, I. (2015). International Banking for a New Century. Paris: Routledge. ISBN 9780415681339
31. Stancu, I. & Rece, D. (2009). The relationship between economic growth and money laundering – a linear regression model. Asociatia Generala a Economistilor din Romania, 9(538), 3-8.
32. Takats, E. (2011). A theory of “Crying Wolf.” The economics of money laundering enforcement. Journal of Law, Economics and Organization, 27(1), 32-78.
33. United Nations Conference on Trade and Development (UNCTAD, 2020). Africa could gain $89 billion annually by curbing illicit financial flows. Available online at: https://unctad.org/news/africa-could-gain-89-billion-annually-curbing-illicit-financial-flows (Accessed June 29, 2021).
34. Wahyuni, S. (2012). Designing qualitative research. London: SAGE Publication Ltd.
35. Zarreh, A., Wan, H. D., Lee, Y., Saygin, C.& Al Jahani, R. (2019). Cybersecurity concerns for total productive maintenance in smart manufacturing systems. Procedia Manufacturing, 38, 532-539.
Copyright (c) 2023 Thatayaone Mpuchane, Tapiwa Gande
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
.jpg)
