Open Access behavioural Biases, Financial Motives, and Literacy in Crypto-Pyramid Schemes Susceptibility: Evidence from a Systematic Review

Main Article Content

Authors: Michael O. Obuya
Authors: Samuel O. Onyuma
DOI: https://doi.org/10.5281/zenodo.21736718

O. Obuya, M., & O. Onyuma, S. (2026). behavioural Biases, Financial Motives, and Literacy in Crypto-Pyramid Schemes Susceptibility: Evidence from a Systematic Review. Journal of Studies in Corporate & Market Finance, 1(01). https://doi.org/10.5281/zenodo.21736718

Abstract

This study employed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines to examine the influence of behavioural biases, financial motives, and financial literacy on participation in crypto-based pyramid schemes. The review included peer-reviewed journal articles, book chapters, and conference papers published from 2023 to 2025. A systematic literature search was conducted in Scopus, Web of Science, and Google Scholar between 20th February 2025 and 28 February 2025 using combinations of the terms behavioural biases, financial motives, and financial literacy with participation in crypto-based pyramid schemes. Retrieved records were imported into Zotero for duplicate removal, followed by title, abstract, and full-text screening against predefined inclusion and exclusion criteria. A total of 25 studies met the eligibility criteria and were synthesised thematically to identify recurring patterns, gaps, and outcomes. The review found that behavioural biases, including overconfidence, herding, framing effects, fear of missing out and greed, strongly increase susceptibility to crypto-based pyramid schemes. Financial motives, particularly the pursuit of high returns, financial hardship, and personal enrichment, further drive participation, while low financial literacy exacerbates vulnerability. The interaction among these factors further strengthens their influence on participation. The study recommends that financial literacy programmes incorporate behavioural training to help individuals recognise and mitigate cognitive biases. Future research should adopt longitudinal and experimental designs to establish causal relationships.

Article Details

References

1. Ahmad, Z. (2025). Investment Scams: The Effect of Bias-Induced Gullibility on Victimization Propensity. Crime, Law and Social Change, 83, 17. https://doi.org/10.1007/s10611-024-10187-1

2. Aren, S., & Nayman Hamamci, H. (2023). Evaluation of Investment Preference with Fantasy, Emotional Intelligence, Confidence, Trust, Financial Literacy and Risk Preference. Kybernetes, 52(12), 6203–6231. https://doi.org/10.1108/K-01-2022-0014

3. Auer, R., & Claessens, S. (2021). Cryptocurrency market reactions to regulatory news 1. In The Routledge handbook of FinTech (pp. 455–468). Routledge.

4. Ayadi, O. F., Paseda, O., Oke, B. O., & Oladimeji, A. (2024). A survey of attitudes, behaviors and experiences of Nigerian investors in cryptocurrencies. Jour. of Inter. and Dig. Econ, 4(2), 83–98. https://doi.org/10.1108/JIDE-11-2023-0023

5. Baltacı, A., & Vural, A. (2025). Anatomy of herd behavior in Ponzi schemes within the scope of marketing mix. Qual. Res. in Fin. Mark, 17(2), 275–291. https://doi.org/10.1108/QRFM-09-2023-0218

6. Barberis, N., & Thaler, R. (2003). A Survey of Behavioral Finance. In G. M. Constantinides, M. Harris, & R. M. Stulz (Eds), Handbook of the Econ of Fin., 1: 1053–1128). . https://doi.org/10.1016/S1574-0102(03)01027-6

7. Barrichello, D., Martin, K., & Bagaskara, J. (2024). Analysis of Determinants Influencing Victims’ Interest in Illegal Investments. Proceedings of the International Conference on Computer and Infor-mation Technology, 1–6. https://doi.org/10.1109/ICCIT62134.2024.10701140

8. Bhadra, S., & Singh, K. N. (2024). Ponzi scheme like investment schemes in India–causes, impact and solution. Jour. of Mon Laund. Cont., 27(2), 348–362. https://doi.org/10.1108/JMLC-02-2023-0040

9. Bhat, A. H., & Kolhe, D. (2024). Crime and Fraud at the Community level: Social Networking Understanding into Economic crimes and Psychology Motivations. Jour of Soc. Sci. and Econ, 3(2), 109–128. https://doi.org/10.61363/g0kb2s44

10. Chandler, J., Cumpston, M., Li, T., Page, M. J., & Welch, V. (2019). Cochrane handbook for systematic reviews of interventions. Hoboken: Wiley, 4(1002), 14651858.

11. Chelin, R. (2021). Africa: New playground for crypto scams and money laundering, https://issafrica.org/iss-today/africa-new-playground-for-crypto-scams-and-money-laundering

12. Constantino, T. D. S. T., Da Silva, A. C. M., & Constantino, M. A. M. D. O. (2024). Ponzi schemes in Brazil: What leads people to still invest in this fraud? Jour. of Fin. Crim., 31(6), 1436–1450. https://doi.org/10.1108/JFC-10-2023-0262

13. Department of Financial Protection and Innovation. (2025). Crypto scams: How to avoid becoming a victim [State of California]. , https://dfpi.ca.gov/news/insights/crypto-scams-how-to-avoid-becoming-a-victim/

14. Doğan, G., Kalayci, K., & Man, P. (2024). Pyramid Schemes. University of Queensland, School of Economics.

15. Dulisse, B. C., Connealy, N., & Logan, M. W. (2024). The influence and role of cryptoculture on target congruence in cryptocurrency investment behavior: A theoretical model. Crim, Law and Soc Chan, 81(4), 421–441. https://doi.org/10.1007/s10611-023-10126-6

16. Egiyi, M. A., & Chin-dengwike, J. (2024). The Psychology Behind Financial Fraud: Unmasking Motives and Warning Signs. James, 4(1), 16–24. https://doi.org/10.5281/zenodo.8287913

17. Federal Bureau of Investigation. (2023). Criptocurrency Fraud Report 2023 (pp. 1–23). Fideral Bureau of Investigation. https://www.ic3.gov/AnnualReport/Reports/2023_IC3CryptocurrencyReport.pdf

18. Garba, K. H., Lazarus, S., & Button, M. (2024). An assessment of convicted cryptocurrency fraudsters. Cur Iss in Crim Just, 1–17. https://doi.org/10.1080/10345329.2024.2403294

19. Ghani, M. T. A., Halim, B. A., Rahman, S. A. A., Abdullah, N. A., Afthanorhan, A., & Yaakub, N. (2023). Overconfidence bias among investors: A qualitative evidence from ponzi scheme case study. Corp and Bus Strat Rev, 4(2), 59–75. https://doi.org/10.22495/cbsrv4i2art6

20. Guyatt, G. H., Oxman, A. D., Kunz, R., Brozek, J., Alonso-Coello, P., Rind, D., & others. (2011). GRADE Guidelines: 1. Introduction—GRADE Evidence Profiles and Summary of Findings Ta-bles. Jour. of Clin. Epidem, 64(4), 383–394. https://doi.org/10.1016/j.jclinepi.2010.04.026

21. Higgins, J. P. T., Thomas, J., Chandler, J., Cumpston, M., Li, T., Page, M. J., & Welch, V. A. (Eds). (2022). Cochrane Handbook for Syst. Rev. of Interven. (6.3). John Wiley & Sons. https://training.cochrane.org/handbook

22. Hong, Q. N., Fàbregues, S., Bartlett, G., Boardman, F., Cargo, M., Dagenais, P., Gagnon, M.-P., Griffiths, F., Nicolau, B., O’Cathain, A., Rousseau, M.-C., Vedel, I., & Pluye, P. (2018). The Mixed Methods Appraisal Tool (MMAT) version 2018 for information professionals and researchers. Educ. for Infor, 34(4), 285–291. https://doi.org/10.3233/EFI-180221

23. Juned, A. M., Ab Aziz, A. A., Sharif, N. A. M., Kamar, N., Shah, M., Yatim, A. I. A., & Fakhruddin, W. F. W. W. (2024). The Language of Lies: An Analysis of Deceptive Linguistic Cues on Malaysian In-vestors’ Decision Making. 8(10), 668–673. https://doi.org/10.47772/IJRISS.2024.8100056

24. KaIneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econ, 47(2), 363–391.

25. Kaiyrbekova, G. (2024). Criminal Legal Measures to Counteract the Activities of Financial Pyramids in the Republic of Kazakhstan. Pakis Jour of Crim, 16(3). https://doi.org/10.62271/pjc.16.3.153.170

26. Kalabeke, W., & Nguyen, L. T. P. (2024). Get-Rich-Quick Syndrome and Ponzi Scheme Investment Intention. 1934–1939.

27. Kayode. P. A., & Adaramola, A. A. O. (2024). Ponzi investment in Nigeria: The greedy quest for wealth in the face of losses. BERJAYA Jour of Serv & Man, 22(7), 67–84.

28. Martín, M. A., Orduna-Malea, E., Thelwall, M., & Delgado López-Cózar, E. (2018). Google Scholar, Web of Science, and Scopus: A systematic comparison of citations in 252 subject cate-gories. Jour. of Info, 12(4), 1160–1177. https://doi.org/10.1016/j.joi.2018.09.002

29. Mintz, Y., Meyer, J., & Bereby-Meyer, Y. (2025). Exploring Suboptimal Investment Behavior in Pyramid Schemes. https://doi.org/10.2139/ssrn.5269483

30. Mireku, K., Appiah, F., & Agana, J. A. (2023). Is There a Link Between Financial Literacy and Financial Behaviour? Cogent Economics & Finance, 11(1), 2188712. https://doi.org/10.1080/23322039.2023.2188712

31. Mukherjee, S., Larkin, C., & Corbet, S. (2021). Cryptocurrency ponzi schemes. Understanding Cryptocurrency Fraud: The Challenges and Headwinds to Regulate Digital Currencies, 2, 111. https://doi.org/10.1515/9783110718485-009

32. Nadeem, N., Saad, A., Aslam, Z., & Naveed, Z. (2025). Technocrime and Student Victimization: An Empirical Analysis of Cryptocurrency Fraud in Multan. Soc. Sci. Spect, 4(2), 47–57. https://doi.org/10.71085/sss.04.02.256

33. Naseem, H., & Musah, M. (2025). Financial Crime in the Age of Cryptocurrency: How Scammers Manipulate Digital Wealth. https://doi.org/10.13140/RG.2.2.30948.28804

34. Nguyen, N. T., Nguyen, A. T., To, H. T. N., & Le, T. T. H. (2024). Why are Vietnamese people susceptible to cryptocurrency Ponzi schemes? Findings from using the PLS-SEM approach. Jour of Fin Crim, 31(1), 158–173. https://doi.org/10.1108/JFC-12-2022-0299

35. Onggowati, M. (2025). The Influence of Financial Literacy, Crypto Literacy, Behavioural Biases, and Perceived Regulatory Environments on Cryptocurrency Adoption: A Comparative Study of Developed and Emerging Markets [Master’s dissertation, University of Roehampton]. https://doi.org/10.2139/ssrn.5332033

36. Pertiwi, D., Kusumawardhani, A., Pratama, J. T. K., & Paul, T. I. S. (2024). Investigating the Impact: Financial Literacy, Socio-Economic Status, and Awareness on Investment Decisions with Moderation Factors. Petra Inter Jour of Bus Stud, 7(1), 19–27. https://doi.org/10.9744/petraijbs.7.1.19-27

37. Prachayanant, P., Kraiwanit, T., & Chutipat, V. (2023). Cryptocurrency gamification: Having fun or making money. Jour of Gov and Reg, 12(2), 184–193. https://doi.org/10.22495/jgrv12i2art17

38. Samanta, N. (2025). Analysing Motivations of Ponzi Victims in West Bengal, India. Human. and Soc. Sci. Commun. 12, 407. https://doi.org/10.1057/s41599-025-04737-8

39. Shefrin, H. (2002). Beyond Greed and Fear: Understanding Behavioral Finance and the Psychology of Investing. Oxford University Press.

40. Sirohi, N., & Misra, G. (2024). Vulnerability of Individuals to Economic Crime and the Role of Financial Literacy in Its Prevention: Evidence from India. Crim. Law and Soc. Chang, 82(1), 165–196. https://doi.org/10.1007/s10611-024-10138-w

41. Tachado, C. (2023). Intentions, expectations, benefits, and effects of investing in Ponzi scheme. Inter Jour of Arts, Sci and Educ, 4(2),. https://mail.ijase.org/index.php/ijase/article/view/251

42. TRM Labs. (2025). 2025 Crypto Crime Report. TRM Labs. https://www.trmlabs.com/resources/reports/2025-crypto-crime-report

43. U.S. Securities and Exchange Commission. (2025). Ponzi Schemes Using Virtual Currencies (Issue 153 (7/13)). https://www.sec.gov/files/ia_virtualcurrencies.pdf

44. Zheng, H., Li, Q., & Xia, C. (2024). Does financial literacy contribute to facilitating residents in safeguarding their rights as financial consumers? A three-stage study based on the perspective of “fraud” phenomenon. Inter Rev of Econ & Fin, 93, 720–735. https://doi.org/10.1016/j.iref.2024.03.053

45. Zuckerman, J., & Stock, M. (2025, April 4). How to Report a Crypto Ponzi Scheme and Earn an SEC Whistleblower Award. https://natlawreview.com/article/how-report-crypto-ponzi-scheme-and-earn-sec-whistleblower-award