Assessing the Dynamics of Fintech and Financial Inclusion in Reducing Inequality in Malaysia: a Bayesian-Wavelet approach
Main Article Content
Abstract
This paper examines the impact of FinTech on financial inclusion and inequality reduction in Malaysia within the framework of SDG 10. Using a Bayesian VAR model and wavelet coherence analysis (2004–2022), the study analyzes dynamic links between FinTech, inclusion, inequality, and growth. A FinTech Adoption Index (PCA) and a novel Financial Inclusion Index are constructed. Results reveal bidirectional causality, with FinTech and inclusion jointly reducing disparities and fostering inclusive growth. Policy implications highlight the need for inclusive ecosystems, literacy programs, and adaptive regulation.
Metrics
Article Details

This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Boulila, H., Metadjer, W., Elsayed, I., & Benbekhti, S. E. (2024). The digital butterfly effect: unleashing the Islamic banking industry in a post-pandemic era. European Journal of Islamic Finance, 11(2), 36–54.
Corrado, G., & Corrado, L. (2017). Inclusive finance for inclusive growth and development. Current Opinion in Environmental Sustainability, 24, 19–23. https://doi.org/10.1016/j.cosust.2016.11.001
Demirgüç-Kunt, A., Klapper, L., Singer, D., Ansar, S., & Hess, J. (2018). The Global Findex Database 2017: Measuring financial inclusion and the fintech revolution. Washington, DC: World Bank.
Demirgüç-Kunt, A., Klapper, L., Singer, D., Ansar, S., & Hess, J. (2018). Opportunities for expanding financial inclusion through digital technology. In Global Findex Database 2017: Measuring financial inclusion and the fintech revolution (pp. 49–65). Washington, DC: World Bank.
Grinsted, A., Moore, J. C., & Jevrejeva, S. (2004). Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Processes in Geophysics, 11(5–6), 561–566. https://doi.org/10.5194/npg-11-561-2004
Hamid, N. A., Suria, K., Jasni, N. S., & Salleh, K. A. M. (2024). Fintech in Malaysia: Navigating challenges and shaping a digital future. Accounting and Finance Research, 13(1), 1–42. https://doi.org/10.5430/afr.v13n1p1
Hatta, M., & Alwi, S. F. S. (2021). Fintech development in financial institutions industry: An empirical study on Malaysia Islamic banks. Journal of Academic Research in Business and Social Sciences, 11(3), 487–499. https://doi.org/10.6007/IJARBSS/v11-i3/9029
Jolliffe, I. T. (2002). Principal component analysis for special types of data. Springer.
Klapper, L., & Singer, D. (2017). The opportunities and challenges of digitizing government-to-person payments. The World Bank Research Observer, 32(2), 211–226. https://doi.org/10.1093/wbro/lkx003
Ozili, P. K. (2018). Impact of digital finance on financial inclusion and stability. Borsa Istanbul Review, 18(4), 329–340. https://doi.org/10.1016/j.bir.2017.12.003
Rua, A., & Nunes, L. C. (2009). International comovement of stock market returns: A wavelet analysis. Journal of Empirical Finance, 16(4), 632–639. https://doi.org/10.1016/j.jempfin.2009.02.002
Sahay, M. R., von Allmen, M. U. E., Lahreche, M. A., Khera, P., Ogawa, M. S., Bazarbash, M., & Beaton, M. K. (2020). The promise of fintech: Financial inclusion in the post COVID-19 era. Washington, DC: International Monetary Fund.
Tian, Q., Lewis‐Beck, C., Niemi, J. B., & Meeker, W. Q. (2024). Specifying prior distributions in reliability applications. Applied Stochastic Models in Business and Industry, 40(1), 5–62. https://doi.org/10.1002/asmb.2825
Torrence, C., & Compo, G. P. (1998). A practical guide to wavelet analysis. Bulletin of the American Meteorological Society, 79(1), 61–78. https://doi.org/10.1175/1520-0477(1998)
Tran, T. K. O., & Dinh, L. Q. (2024). Digital financial inclusion, financial stability, and sustainable development: Evidence from Vietnam. Sustainable Development, 32(6), 6324–6338. https://doi.org/10.1002/sd.2912
Vacha, L., & Barunik, J. (2012). Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis. Energy Economics, 34(1), 241–247. https://doi.org/10.1016/j.eneco.2011.10.007
Yoon, J. (2015). Partial least squares and principal component analysis with non-metric variables for composite indices. Computational Statistics, 30(2), 573–593. https://doi.org/10.1007/s00180-014-0517-9