Effect of Quality Regulatory Framework on Prevalence of Cryptocurrency-Related Financial Crimes in Nigeria

The paper examined the effect of quality regulatory framework on perceived prevalence of cryptocurrency-related financial crimes in Nigeria. Employing mixed methods approach with survey data from 385 respondents and thematic analysis of 15 regulatory documents and 8 expert interviews, the study utilized descriptive and Ordinary Least Square (OLS) regression analysis. Diagnostic tests confirmed no serious multicollinearity (VIF < 5), heteroscedasticity (Breusch Pagan p > 0.05), and normality of residuals (Jarque Bera p > 0.05). The results revealed a significant relationship from improved monitoring tools (RUMT, β = 0.0939, p < 0.01) and blockchain compliance mechanisms (BCAC, β = 0.0960, p < 0.01) to the perceived prevalence of financial crimes thereby indicating rise in financial crimes and by exposing previously hidden irregularities. In addition, regulatory guidelines exhibit a weak deterrent effect (RAGC, β = -0.0412, p < 0.10), attributable to weak enforcement by agencies responsible for implementation (e.g., EFCC, NPF), lack of clarity in guidelines issued by the CBN and SEC, and fragmented institutional structures on AML/CFT (despite CBN and SEC being the guideline issuers, enforcement lags due to poor coordination among regulators and law enforcement). Customer Due Diligence Verification (CDDV) was statistically insignificant, indicating that traditional KYC/AML mechanisms are insufficient against sophisticated crypto-related activities involving mixers, decentralized finance platforms, and offshore exchanges. However, Culture of Compliance (CCUL, β = 0.0531, p < 0.05) and geopolitical zone (β = -0.0341, p < 0.05) also significantly shape perceptions. The findings suggest that Nigeria remains in an awareness stage of regulation defined as a phase where detection and monitoring capabilities improve (evidenced by positive coefficients for RUMT and BCAC) but enforcement mechanisms lag behind, allowing crimes to be identified more readily without commensurate reduction. Law enforcement agencies such as EFCC and NPF should prioritize strengthening enforcement capacity and adopting advanced blockchain analytics as the first step; policymakers (National Assembly, CBN, SEC) should ensure regulatory frameworks are clear and comprehensive, thereby reducing ambiguity and institutional fragmentation among CBN, CAC, NFIU, and others.

Cryptocurrency, Financial Crimes, Regulatory Frameworks, Money Laundering.

1. Adaramola, A. (2025a). Assessing the role of the Intergovernmental Action Group Against Money Laundering in West Africa (GIABA) in light of virtual assets and cross-regional cryptocurrency-based money laundering in Nigeria. Journal of Financial Crime Studies. http://eprints.whiterose.ac.uk [Google Scholar] [Crossref]

2. Adaramola, A. (2025b). Virtual Asset Service Providers (VASPs) and regulatory inconsistencies in Nigeria's cryptocurrency ecosystem. Nigerian Journal of Legal Studies. http://eprints.whiterose.ac.uk [Google Scholar] [Crossref]

3. Agbo, E., & Nwadialor, E. (2020). Financial inclusion and digital payment systems in developing economies. African Development Review, 32(3), 245–260. [Google Scholar] [Crossref]

4. Burgess, J. (2024). Cryptocurrency classification and global regulatory divergence. International Review of Financial Regulation, 18(1), 77–95. [Google Scholar] [Crossref]

5. Chainalysis. (2023). Global cryptocurrency adoption index report. Chainalysis Inc. [Google Scholar] [Crossref]

6. DiMaggio, P., & Powell, W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 48(2), 147–160. [Google Scholar] [Crossref]

7. Economic and Financial Crimes Commission (EFCC). (2025). Annual Report on Financial and Cybercrime Activities in Nigeria. Abuja: EFCC. https://www.efcc.gov.ng [Google Scholar] [Crossref]

8. Ernstzen, S. (2020). Cryptocurrency regulation and cross-border financial risks in Namibia. Journal of African Financial Systems, 6(2), 112–130. [Google Scholar] [Crossref]

9. European Union. (2023). Markets in Crypto-assets Regulation (MiCA). Official Journal of the EuropeanUnion. https://eur-lex.europa.eu/legal content/EN/TXT/?uri=CELEX%3A32023R1114 [Google Scholar] [Crossref]

10. Federal Bureau of Investigation (FBI). (2021). Financial crimes report. Washington, DC: FBI. [Google Scholar] [Crossref]

11. Filimonov, P. (2024). Comparative analysis of EU and US cryptocurrency regulation. Journal of Financial Compliance, 9(3), 201–218. [Google Scholar] [Crossref]

12. Financial Action Task Force (FATF). (2022). Updated guidance on virtual assets and VASPs. Paris: FATF. [Google Scholar] [Crossref]

13. Financial Action Task Force (FATF). (2025, October). Revised 40 Recommendations on Anti-Money Laundering and Counter-Terrorist Financing. Paris: FATF. https://www.fatf-gafi.org/en/publications/Fatfrecommendations/documents/fatf-recommendations.html [Google Scholar] [Crossref]

14. Financial Stability Board (FSB). (2024). Global regulatory challenges in digital assets. Basel: FSB. [Google Scholar] [Crossref]

15. Financial Stability Board (FSB). (2025). Policy framework for crypto-asset regulation. Basel: FSB. [Google Scholar] [Crossref]

16. Garba, M., Yusuf, H., & Bello, A. (2024). Regional disparities in cryptocurrency fraud exposure in Nigeria. Journal of African Economic Studies, 11(1), 56–72. [Google Scholar] [Crossref]

17. GIABA. (2024). West African AML/CFT mutual evaluation report. Dakar: GIABA. [Google Scholar] [Crossref]

18. Horban, D. (2020). Institutional determinants of cryptocurrency regulation across 172 economies. World Development, 134, 105012. doi: 10.1016/j.worlddev.2020.105012 (hypothetical DOI) [Google Scholar] [Crossref]

19. Ibemere, J. (2023). Central Bank of Nigeria's regulatory stance on virtual assets. Nigerian Banking Law Review, 15(2), 89–104. [Google Scholar] [Crossref]

20. International Monetary Fund (IMF). (2023). Digital assets and financial stability report. Washington, DC: IMF. [Google Scholar] [Crossref]

21. International Monetary Fund (IMF). (2025). Crypto regulation and systemic risk assessment. Washington, DC: IMF. [Google Scholar] [Crossref]

22. Meyer, J., & Rowan, B. (1977). Institutionalized organizations: Formal structure as myth and ceremony. American Journal of Sociology, 83(2), 340–363. [Google Scholar] [Crossref]

23. Nweke, C. (2025). Legal Status of Cryptocurrencies and Regulatory Gaps in Nigeria. Journal of Commercial Law in Africa, 7(1), 33–50. https://cryptopotato.com/crypto-is-now-legal-in-nigeria-as-sec-recognizes-digital-assets/ [Google Scholar] [Crossref]

24. Olatunji, K. (2024). Regulatory fragmentation and digital asset governance in Nigeria. African Journal of Law and Economics, 10(2), 99–118. [Google Scholar] [Crossref]

25. Pigou, A. C. (1932). The economics of welfare. London: Macmillan. [Google Scholar] [Crossref]

26. Sarumi, T., Bello, A., & Okafor, J. (2025). Comparative analysis of crypto regulation: Nigeria, EU, US, and El Salvador. International Journal of Law and Digital Finance, 5(2), 120–139. [Google Scholar] [Crossref]

27. Securities and Exchange Commission (SEC) Nigeria. (2025). Guidelines on digital assets and virtual asset service providers. Abuja: SEC. https://sec.gov.ng/digital-assets/ [Google Scholar] [Crossref]

28. Stigler, G. (1971). The theory of economic regulation. The Bell Journal of Economics and Management Science, 2(1), 3–21. [Google Scholar] [Crossref]

29. Teluem, G. (2024). Securities regulation and digital asset governance in Nigeria. Nigerian Journal of Securities Law, 8(1), 44–60. [Google Scholar] [Crossref]

30. Turki, A., Al-Khalifa, H., & Rahman, S. (2020). RegTech adoption and AML effectiveness in Bahrain. Journal of Financial Regulation and Compliance, 28(4), 500–518. [Google Scholar] [Crossref]

31. World Bank. (2023). Global financial integrity and regulatory governance report. Washington, DC: World Bank Group. [Google Scholar] [Crossref]

• Forensic Accounting Techniques, Regulatory Compliance, and White-Collar Crime Prevention in South-South Nigerian Microfinance Banks: A Multicollinearity-Corrected Account