Journal Press India^®

Author Details ( * ) denotes Corresponding author

Financial Technology (Fintech) is a digital business model that caters to financial requirements globally and has evolved into an inseparable component of the financial services sector. The surge of Fintech across nations and regions, is largely unregulated which calls for a cautionary approach to its uses and benefits. Fintech relies heavily on data, and cyber-attacks can severely compromise customer privacy and data security. Building on the works of several studies that customers with greater financial literacy tend to use more Fintech services, this study focuses on the security risk perception of financially literate Fintech customers. Furthermore, using a multi-model evaluation with the Smart PLS software, it investigates the moderating role of gender in evaluating the relationship between financia literacy and security risk erception. The study contributes to existing academic debates and paves the way for further research.

Keywords

Financial Technology; Perceived Risk; Financial Literacy; Multi Method; Smart PLS

1. Afif, N., & Purwantini, A. H. (2022). The paradox of perceived risk and trust on intention to use fintech payment: Evidence in MSMEs. In 3^rd Borobudur International Symposium on Humanities and Social Science 2021 (BIS-HSS 2021) (pp. 645-648). Atlantis Press.
2. Albort-Morant, G., Leal-Millán, A., & Cepeda-Carrión, G. (2016). The antecedents of green innovation performance: A model of learning and capabilities. Journal of Business Research, 69(11), 4912-4917.
3. Ali, M., Raza, S. A., Khamis, B., Puah, C. H., & Amin, H. (2021). How perceived risk, benefit and trust determine user Fintech adoption: A new dimension for Islamic finance. Foresight, 23(4), 403-420.
4. Alwi, S., Salleh, M. N. M., Razak, S. E. A., & Naim, N. (2019). Consumer acceptance and adoption towards payment-type fintech services from Malaysian perspective. International Journal of Advanced Science and Technology, 28(15), 148–163.
5. Andrew, J. V., Ambad, S. A., Abdullah, N. S. W., Nordin, S., & Esther,T. K. (2021). A systematic review of e-wallet usage intention: Integrating UTAUT2 with perceived security. Jurnal Intelek, 16(1), 124–133. Retrieved from https://doi.org/10.24191/ji.v16i1.372
6. Behrman, J. R., Mitchell, O. S., Soo, C. K., & Bravo, D. (2012). How financial literacy affects household wealth accumulation. American Economic Review, 102(3), 300–304. Retrieved from https://doi.org/10.1257/AER.102.3.300    
7. Belanche, D., Guinalíu, M., & Albás, P. (2022). Customer adoption of p2p mobile payment systems: The role of perceived risk. Telematics and Informatics, 72, 101851. Retrieved from https://doi.org/10.1016/j.tele.2022.101851
8. Bommer, W. H., Milevoj, E., & Rana, S. (2023). A meta-analytic examination of the antecedents explaining the intention to use fintech. Industrial Management & Data Systems, 123(3), 886-909.
9. Boolaky, A., Mauree-Narrainen, D., & Padachi, K. (2021). Financial literacy of young professionals in the context of financial technology developments in Mauritius. Journal of Social Economics Research, 8(2), 119-134.
10. Chan, R., Troshani, I., Rao Hill, S., & Hoffmann, A. (2022). Towards an understanding of consumers’ FinTech adoption: The case of open banking. International Journal of Bank Marketing, 40(4), 886-917.
11. Das, S. R. (2019). The future of Fintech. Financial Management, 48(4), 981–1007. Retrieved from https://doi.org/10.1111/fima.12297
12. Dattalo, P. (2008). Determining sample size, balancing power, precision, and practicality. Oxford University Press: USA.
13. Dospinescu, O., Dospinescu, N., & Agheorghiesei, D. T. (2021). Fintech services and factors determining the expected benefits of users: Evidence in romania for millennials and generation Z. E&M: Ekonomie a Management, 24(2), 101–118. Retrieved from https://doi.org/10.15240/tul/001/2021-2-007
14. Ernst & Young. (2019). Global FinTech adoption index 2019. Ernst & Young. Retrieved from https://www.ey.com/en_gl/ey-global-fintech-adoption-index
15. Ferdaous, D. J., & Rahman, M. N. (2021). Banking goes digital: Unearthing the adoption of fintech by Bangladeshi households. Journal of Innovative Business Studies, 1(1), 7-42.
16. Gabor, D., & Brooks, S. (2017). The digital revolution in financial inclusion: international development in the fintech era. New Political Economy, 22(4), 423–436. Retrieved from https://doi.org/10.1080/13563467.2017.1259298  
17. Garson, G. D. (2016). Partial least squares: Regression & structural equation model. Statistical Associates Publishers: Asheboro.
18. Ghafoor, S., Duffour, K. A., Khan, U. F., & Khan, M. K. (2022). Social wellbeing, board-gender diversity, and financial performance: Evidence from Chinese Fintech companies. Frontiers in Psychology, 13, 862897.
19. Gomber, P., Kauffman, R. J., Parker, C., & Weber, B. W. (2018). On the fintech revolution: Interpreting the forces of innovation, disruption, and transformation in financial services. Journal of Management Information Systems, 35(1). Retrieved from https://doi.org/10.1080/07421222.2018.1440766
20. Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2017^th ed.). Sage.
21. Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19(2), 139-152.
22. Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long range planning, 46(1-2), 1-12.
23. Hair, J. F., Sarstedt, M., Pieper, T. M., & Ringle, C. M. (2012). The use of partial least squares structural equation modelling in strategic management research: A review of past practices and recommendations for future applications. Long range planning, 45(5-6), 320-340.
24. Hasan, R., Ashfaq, M., & Shao, L. (2021). Evaluating drivers of fintech adoption in the Netherlands. Global Business Review. Retrieved from https://doi.org/10.1177/09721509211027402
25. Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In New challenges to international marketing (Vol. 20, pp. 277-319). Emerald Group Publishing Limited.
26. Henseler, J., Ringle, C. M., & Sarstedt, M. (2016). Testing measurement invariance of composites using partial least squares. International Marketing Review, 33(3), 405-431.
27. Herdinata, C. (2020). The effect of regulation, collaboration, and financial literacy on financial technology adoption. Expert Journal of Business and Managemen, 8(2), 131–138.
28. Irawan, N. N., & Matoati, R. (2021). The influence of financial literacy and behavior in using fintech payments on the financial management of Jabodetabek students. The Management Journal of Binaniaga, 6(2), 117–132. Retrieved from https://doi.org/10.33062/mjb.v6i2.459
29. Ismail, N., Roslan, N. A., Fauzi, N. A. M., Husin, M. M., Amalina, R. N., Asmidar, M. F. N., & Husin, M. (2018). Perceived security and consumer trust in adoption of fintech service. European Proceedings of Social and Behavioural Sciences, 44. Retrieved from https://www.europeanproceedings.com/article/10.15405/epsbs.2018.07.02.70
30. Jangir, K., Sharma, V., Taneja, S., & Rupeika-Apoga, R. (2022). The moderating effect of perceived risk on users’ continuance intention for fintech services. Journal of Risk and Financial Management, 16(1), 16-21.
31. Kang, J. (2018). Mobile payment in Fintech environment: trends, security challenges, and services. Human-Centric Computing and Information Sciences, 8(1), 1–16. Retrieved from https://doi.org/10.1186/S13673-018-0155-4
32. Khera, P., Ogawa, S., Sahay, R. & Vasishth, M. (2022). Women in fintech: As leaders and users. IMF Working Paper No. 2022/140. Retrieved from https://ssrn.com/abstract=4171846
33. Kock, N. (2020). Multilevel analyses in PLS-SEM: An anchor-factorial with variation diffusion approach. Data Analysis Perspectives Journal, 1(2), 1-6.
34. Koskelainen, T., Kalmi, P., Scornavacca, E., & Vartiainen, T. (2023). Financial literacy in the digital age—A research agenda. Journal of Consumer Affairs, 57(1), 507-528.
35. Laksamana, P., Suharyanto, S., & Cahaya, Y. F. (2023). Determining factors of continuance Intention in mobile payment: fintech industry perspective. Asia Pacific Journal of Marketing and Logistics, 35(7), 1699-1718.
36. Lee, I., & Shin, Y. J. (2018). Fintech: Ecosystem, business models, investment decisions, and challenges. Business horizons, 61(1), 35-46.
37. Lim, S. H., Kim, D. J., Hur, Y., & Park, K. (2019). An empirical study of the impacts of perceived security and knowledge on continuous intention to use mobile fintech payment services. International Journal of Human–Computer Interaction, 35(10), 886-898.
38. Mainardes, E. W., Costa, P. M. F., & Nossa, S. N. (2022). Customers’ satisfaction with fintech services: Evidence from Brazil. Journal of Financial Services Marketing, 28(2), 378-395.
39. Majid, R., & Nugraha, R. A. (2022). Crowdfunding and Islamic securities: The role of financial literacy. Journal of Islamic Monetary Economics and Finance, 8(1). Retrieved from https://doi.org/10.21098/jimf.v8i1.1420
40. Mascarenhas, A. B., Perpétuo, C. K., Barrote, E. B., & Perides, M. P. (2021). The influence of perceptions of risks and benefits on the continuity of use of fintech services. BBR. Brazilian Business Review, 18, 1-21.
41. Mazambani, L., & Mutambara, E. (2020). Predicting FinTech innovation adoption in South Africa: The case of cryptocurrency. African Journal of Economic and Management Studies, 11(1), 30-50.
42. Meredith, W. (1993). Measurement invariance, factor analysis and factorial invariance. Psychometrika, 58(4). Retrieved from https://doi.org/10.1007/BF02294825
43. Moenjak, T., Kongprajya, A., & Monchaitrakul, C. (2020). Fintech, financial literacy, and consumer saving and borrowing: The case of Thailand. In ADBI Working Paper Series (Issue 1100). Retrieved from https://www.adb.org/sites/default/files/publication/575576/adbi-wp1100.pdf
44. Morgan, P. J., & Trinh, L. Q. (2019). Fintech and financial literacy in the lao PDR. Retrieved from https://doi.org/10.2139/ssrn.3398235
45. Nangin, M. A., Barus, I. R. G., & Wahyoedi, S. (2020). The effects of perceived ease of use, security, and promotion on trust and its implications on fintech adoption. Journal of Consumer Sciences, 5(2), 124-138.
46. Nathan, R. J., Setiawan, B., & Quynh, M. N. (2022). Fintech and financial health in Vietnam during the COVID-19 pandemic: In-depth descriptive analysis. Journal of Risk and Financial Management, 15(125), 1-19.
47. Nguyen, T. A. N. (2022). Does financial knowledge matter in using fintech services? Evidence from an emerging economy. Sustainability (Switzerland), 14(9). Retrieved from https://doi.org/10.3390/su14095083
48. Noreen, M., Ghazali, Z., & Shahin, M. (2021). The impact of perceived risk and trust on adoption of mobile money services: An empirical study in Pakistan. Journal of Asian Finance, 8(6), 347–0355. Retrieved from https://doi.org/10.13106/jafeb.2021.vol8.no6.0347
49. Nurlaily, F., Aini, E. K., & Asmoro, P. S. (2021). What determines generation Z continuance intention of fintech? The moderating effect of gender. Proceedings of the 3rd Annual International Conference on Public and Business Administration (AICoBPA 2020), 191. Retrieved from https://doi.org/10.2991/aebmr.k.210928.055
50. Panos, G. A., & Wilson, J. O. S. (2020). Financial literacy and responsible finance in the FinTech era: Capabilities and challenges. European Journal of Finance, 26(4–5), 297–301. Retrieved from https://doi.org/10.1080/1351847X.2020.1717569
51. Razzaque, A., & Hamdan, A. (2020). Role of financial technology fintech: A survey. Advances in Intelligent Systems and Computing, 1153 AISC, 112–117. Retrieved from https://doi.org/10.1007/978-3-030-44289-7_11
52. Reynon, M. K., Bulatao, P. C., Vergel, J. A., Yabut, L. A., & Grimaldo, J. (2022). Consumer’s attitude on online payment systems as driven by risks. Journal of Business and Management Studies, 4(2). Retrieved from https://doi.org/10.32996/jbms.2022.4.2.2
53. Richter, N. F., Cepeda-Carrión, G., Roldán Salgueiro, J. L., & Ringle, C. M. (2016). European management research using partial least squares structural equation modeling (PLS-SEM). European Management Journal, 34(6), 589-597.
54. Ryu, H. S. (2018). What makes users willing or hesitant to use Fintech? The moderating effect of user type. Industrial Management and Data Systems, 118(3), 541–569. Retrieved from https://doi.org/10.1108/IMDS-07-2017-0325
55. Saleem, A. (2021). Fintech revolution, perceived risks and fintech adoption: Evidence from financial industry of Pakistan. International Journal of Multidisciplinary and Current Educational Research (IJMCER), 3(3), 191-205.
56. Sarstedt, M., Ringle, C. M., Smith, D., Reams, R., & Hair Jr, J. F. (2014). Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers. Journal of family business strategy, 5(1), 105-115.
57. Satterthwaite, F. E. (1946). An approximate distribution of estimates of variance components. Bulletin, 2(6). Retrieved from https://about.jstor.org/terms
58. Savitha, B., Hawaldar, I. T., & Kumar, N. (2022). Continuance intentions to use FinTech peer-to-peer payments apps in India. Heliyon, 8(11), e11654.
59. Solarz, M., & Swacha-Lech, M. (2021). Determinants of the adoption of innovative fintech services by millennials. E&M: Ekonomie a Management, 24(3), 149–166. Retrieved from https://doi.org/10.15240/TUL/001/2021-3-009
60. Stewart, H., & Jürjens, J. (2018). Data security and consumer trust in FinTech innovation in Germany. Information and Computer Security, 26(1), 109–128.
61. Tang, K. L., Ooi, C. K., & Chong, J. B. (2020). Perceived risk factors affect intention to use FinTech. Journal of Accounting and Finance in Emerging Economies, 6(2), 453-463.
62. Tok, Y. W., & Heng, D. (2022). Fintech: Financial inclusion or exclusion? International Monetary Fund.
63. Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1). Retrieved from https://doi.org/10.1177/109442810031002
64. Wold, H. (1980). Model construction and evaluation when theoretical knowledge is scarce: Theory and application of partial least squares. In Evaluation of econometric models (pp. 47-74). Academic Press
65. Xie, J., Ye, L., Huang, W., & Ye, M. (2021). Understanding fintech platform adoption: Impacts of perceived value and perceived risk. Journal of Theoretical and Applied Electronic Commerce Research, 16(5). Retrieved from https://doi.org/10.3390/jtaer16050106
66. Yoshino, N., Morgan, P. J., & Long, T. Q. (2020). Financial Literacy and Fintech Adoption in Japan. Asian Development Bank Institute Working Paper 1095 (Issue 1095). Retrieved from https://www.adb.org/publications/financial-literacy-fintech-adoption-japan