Wide-spread financial exclusion and the inability of banks to meet the customers’ expectations in service delivery in Africa have made most central banks seek technology-enabled solutions, especially as the global trend moves towards diversifying the range of financial service provider types. Some authors attributed these problems to the significant financial infrastructural gap in Africa. This study, therefore, investigated the determinants of fintech spreads in a panel of five emerging, 24 frontier, and three fragile African economies from 2002 – 2018. The dynamic panel system GMM estimation technique based on the epidemic and rank theories revealed heterogeneity and significant difference in internet and mobile banking penetration rate among economy types in Africa, with emerging markets reporting higher intercept and lower slope than frontiers and fragile markets. Also, information spread promoted penetration across units; whereas, population growth and literacy only increased it among frontiers and fragile economies but dampened it in emerging economies. This means that users of fintech among emerging markets began to diversify to new innovations aside from those used in this study, hence the decline. Moreover, Africa’s average fintech adoption rate stood at 24%; in South Africa and Morocco, it stood at 43% and 40%, respectively, compared to the global benchmark of 33%. We, therefore, recommend that banks should collaborate with fintech companies to enhance their benefits in Africa.

1. Alexander, A. J., Shi, L., & Solomon, B. (2017). How fintech is reaching the poor in Africa and Asia : A start - up perspective. International Finance Corporation, World Bank Group. https://openknowledge.worldbank.org/handle/10986/30360
2. Andrianaivo, M., & Kpodar, K. (2012). Mobile phones, financial inclusion, and growth. Review of Economics and Institutions, 3(2), Article 4. http://www.rei.unipg.it/rei/article/view/75
3. Arellano, M., & Bond, S. (1991). Some tests of specification for panel data : Monte Carlo evidence and an application to employment equations. The Review of Economic Studies, 58(2), 277–297. https://doi.org/10.2307/2297968
4. Arellano, M., & Bover, O. (1995). Another look at the instrumental variable estimation of error-components models. Journal of Econometrics, 68(1), 29–51. https://doi.org/10.1016/0304-4076(94)01642-D
5. Bhatt, N., Patel, R., & Kaur, A. (2020). A study of ICT adoption and its impact on selected MFIs of Gujarat. Indian Journal of Finance, 14(2), 7–20. https://doi.org/10.17010/ijf/2020/v14i2/150553
6. Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115–143. https://doi.org/10.1016/S0304-4076(98)00009-8
7. Bond, S.R., Hoeffler, A., & Temple, J.R. (2001). GMM estimation of empirical growth models. https://ssrn.com/abstract=290522
8. Bowmans. (2017). Fintech in Africa: Unpacking risk and regulation. https://www.bowmanslaw.com/wp-content/uploads/2017/10/Fintech-In-Africa-Conference-Summary.pdf
9. Caselli, F., Esquivel, G., & Lefort, F. (1996). Reopening the convergence debate: A new look at cross-country growth empirics. Journal of Economic Growth, 1(3), 363–389. https://link.springer.com/article/10.1007/BF00141044
10. Demirguc-Kunt, A., Klapper, L., Singer, D., & Van Oudheusden, P. (2015). The Global Findex Database 2014: Measuring financial inclusion around the world (The World Bank Policy Research Working Paper No. 7255). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2594973
11. EFInA. (2010). EFInA access to financial services in Nigeria 2010 survey. https://efina.org.ng/wp-content/uploads/2018/12/EFInAAccess-to-Financial-Services-in-Nigeria-2010-surveyKey-Findings.pdf
12. Ernst & Young. (2017). EY fintech adoption index 2017: The rapid emergence of fintech. https://assets.ey.com/content/dam/ey-sites/ey-com/en_gl/topics/banking-and-capital-markets/ey-fintech-adoption-index-2017.pdf?download
13. Escobar-Rodríguez, T., & Romero-Alonso, M. (2014). The acceptance of information technology innovations in hospitals: Differences between early and late adopters. Behaviour & Information Technology, 33(11), 1231–1243. https://doi.org/10.1080/0144929X.2013.810779
14. Gourlay, A. R., & Pentecost, E. J. (2002). The impact of network effects on technology adoption: An empirical analysis. The Journal of Manchester School, 70(2), 185 –203.
15. Hall, C. M. (2011). Consumerism, tourism and voluntary simplicity: We all have to consume, but do we really have to travel so much to be happy? Tourism Recreation Research, 36(3), 298–303. https://doi.org/10.1080/02508281.2011.110816751
16. International Monetary Fund. (2018). Financial system soundness. http://www.imf.org/en/About/Factsheets/Financial-System-Soundness
17. Keller, W. (2004). International technology diffusion. Journal of Economic Literature, 42(3), 752–782. http://dx.doi. org/10.1257/0022051042177685
18. Khalifa, A. B. (2016). Determinants of information and communication technologies adoption by Tunisian firms. Journal of Innovation Economics & Management, 2, 151 –177. https://www.cairn.info/revue-journal-of-innovation-economics-2016-2-page-151.htm
19. Kneller, R., Pantea, S., & Upward, R. (2010, August). Does absorptive capacity affect who benefits from international technology transfer? In, Twelfth Annual Conference. https://www.knowledge4all.com/Temp/Files/683babf9-bffc-464d-bd74-22837481529e.pdf
20. Kuri, P. K., & Laha, A. (2011). Determinants of financial inclusion : A study of some selected districts of West Bengal, India. Indian Journal of Finance, 5(8), 29–36. http://www.indianjournaloffinance.co.in/index.php/IJF/article/view/72491
21. Legland, P., & Schneider, D. T. (2016). Can equity crowdfunding crowd-out other alternative sources of finance? https://www.vernimmen.net/ftp/160912_Thesis_David_Schneider_vF.pdf
22. Patel, R., & Patel, N. (2021). Does microfinance empower women from economic, social, and political perspectives ? : Empirical evidence from rural Gujarat. Prabandhan: Indian Journal of Management, 14(3), 32 –48. https://doi.org/10.17010/pijom/2021/v14i3/158154
23. Poushter, J. (2016). Smartphone ownership and internet usage continues to climb in emerging economies. Pew Research Center, 22(1), 1–44. https://www.diapoimansi.gr/PDF/pew_research%201.pdf
24. Siddiqui, T. A., & Siddiqui, K. I. (2020). Telecommunication, socioeconomic, and financial inclusion: An empirical evidence from Bihar. Prabandhan: Indian Journal of Management, 13(10–11), 46–61. https://doi.org/10.17010/pijom/2020/v13i10-11/156008
25. The World Bank. (2018). World development indicators (2018). http://data.worldbank.org/region/sub-saharan-africa.
26. Vodafone. (2016, April 25). Vodafone M-Pesa reaches 25 million customers milestone. https://www.vodafone.com/news/press-release/mpesa-25million