Reshaping Fintech: Unveiling Recent Developments on Fintech Integration
Keywords:
Fintech, Financial technology, Fintech Integration, VOS viewer, BibliometricAbstract
The term FinTech integration refers to a process of amending financial services with the assistance of technology for sure. In other words, the concept translates as the application of technology to the well-established financial system to achieve superior efficiency, accessibility, and overall client experience. This research paper explores the phenomenon of FinTech integration by conducting a systematic mapping study, offering insights into the current trends and future prospects of research into this dynamic area. The examination had a coverage from numerous databases, namely Lens, Scopus, Xplore, and ACM to conduct a comprehensive review of all FinTech-related publications published in the period from 2010 to 2024. As the acquired data indicated a vast increase in the number of FinTech studies, specifically in the domain of Fintech integration, Fintech development, and Fintech adoption. In particular, a bibliometric analysis was performed to collect data on 1,013 research articles from the Lens database, selecting the most relevant documents. Furthermore, the method allowed for the mapping of the temporal scope of FinTech research, offering insights into the most common most types of journals, prolific authors and nations, as well as revealing the most frequent keywords and research areas. Likewise, revealing into the keyword co-occurrence network was created using the software program VOS viewer to showcase the relationships between the various themes of the collected literature. As a result, the research shed light on the rapid expansion of FinTech research in recent years, exposing the most prominent scholars, publications, and countries, as well as identifying upcoming trends in FinTech integration research. Ultimately, the significance of this study is not only in its provision of a coherent guide for those interested in learning more about the FinTech domain. It provides the research roadmap for further exploration within this multifaceted area of the integration of financial technology and its effect upon all participants across the financial field.
References
Cai, C.W., Disruption of financial intermediation by FinTech: a review on crowdfunding and blockchain. Accounting & Finance, 2018. 58(4): p. 965-992.
Aysan, A.F. and Z. Nanaeva, Fintech as a financial disruptor: A bibliometric analysis. FinTech, 2022. 1(4): p. 412-433.
Team, R.C., Available online: https://www. R-project. org/(accessed on 20 August 2021), 2019.
Christensen, C.M., M. Raynor, and R. McDonald, 17. Disruptive innovation. Harvard business review, 2015. 93(12): p. 44-53.
Siek, M. and A. Sutanto. Impact analysis of fintech on banking industry. in 2019 international conference on information management and technology (ICIMTech). 2019. IEEE.
Aysan, A. and Z. Nanaeva, Fintech as a Financial Disruptor: A Bibliometric Analysis. FinTech 2022, 1, 412–433. 2022, s Note: MDPI stays neutral with regard to jurisdictional claims in published ….
Lee, I. and Y.J. Shin, Fintech: Ecosystem, business models, investment decisions, and challenges. Business horizons, 2018. 61(1): p. 35-46.
Sahni, N. and K. Lyne-Smith, Metaverse: A new world of opportunities. CIO Academy. HSBC, 2022.
Donthu, N., et al., How to conduct a bibliometric analysis: An overview and guidelines. Journal of business research, 2021. 133: p. 285-296.
Shibata, N., et al., Detecting emerging research fronts based on topological measures in citation networks of scientific publications. Technovation, 2008. 28(11): p. 758-775.
Aria, M. and C. Cuccurullo, bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of informetrics, 2017. 11(4): p. 959-975.
Wu, P.-S., Fintech trends relationships research: A bibliometric citation meta-analysis. 2017.
Janik, A., A. Ryszko, and M. Szafraniec, Scientific landscape of smart and sustainable cities literature: A bibliometric analysis. Sustainability, 2020. 12(3): p. 779.
Hasan, M.M., et al., An Action Design Research Study on Design Principles for Decision-Making Enhanced by Artificial Intelligence. American Journal of Industrial and Business Management, 2025. 15(1): p. 108-121.
Hasan, M.M., et al., Applying Generative mock Neuro Forge Networks for Synthetic Data Generation in AI Healthcare Systems. Journal of International Crisis and Risk Communication Research, 2024. 7(S12): p. 1257.
Islam, M.A., et al., Artificial intelligence in digital marketing automation: Enhancing personalization, predictive analytics, and ethical integration. Edelweiss Applied Science and Technology, 2024. 8(6): p. 6498-6516.
Jahan, I., et al., Comparative analysis of machine learning algorithms for sentiment classification in social media text. World J. Adv. Res. Rev, 2024. 23(3): p. 2842-2852.
Rabby, H.R., et al. Coronavirus Disease Outbreak Prediction and Analysis Using Machine Learning and Classical Time Series Forecasting Models. in 2024 International Conference on Artificial Intelligence and Quantum Computation-Based Sensor Application (ICAIQSA). 2024. IEEE.
Talukder, T., et al., An Examination of How Social Media Participation and Customer Satisfaction Affect the Likelihood that a Business Will Make Another Transaction in the Hospitality Sector. Open Access Library Journal, 2025. 12(1): p. 1-15.
Mueller, L., et al., Navigating role identity tensions—IT project managers’ identity work in agile information systems development. European Journal of Information Systems, 2025. 34(2): p. 383-406.
Masud, S.B., et al., Understanding the financial transaction security through blockchain and machine learning for fraud detection in data privacy and security. Available at SSRN 5164958, 2024.
Prova, N., Detecting ai generated text based on nlp and machine learning approaches. arXiv preprint arXiv:2404.10032, 2024.
Prova, N.N.I. Healthcare Fraud Detection Using Machine Learning. in 2024 Second International Conference on Intelligent Cyber Physical Systems and Internet of Things (ICoICI). 2024. IEEE.
Prova, N.N.I. Advanced Machine Learning Techniques for Predictive Analysis of Health Insurance. in 2024 Second International Conference on Intelligent Cyber Physical Systems and Internet of Things (ICoICI). 2024. IEEE.
Prova, N.N.I. Improved Solar Panel Efficiency through Dust Detection Using the InceptionV3 Transfer Learning Model. in 2024 8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud)(I-SMAC). 2024. IEEE.
Prova, N.N.I. Garbage Intelligence: Utilizing Vision Transformer for Smart Waste Sorting. in 2024 Second International Conference on Intelligent Cyber Physical Systems and Internet of Things (ICoICI). 2024. IEEE.
Prova, N.N.I. Enhancing Fish Disease Classification in Bangladeshi Aquaculture through Transfer Learning, and LIME Interpretability Techniques. in 2024 4th International Conference on Sustainable Expert Systems (ICSES). 2024. IEEE.
Prova, N.N.I. Empowering Breast Cancer Detection: A Novel Hybrid Transfer Learning Approach with Aquila Optimizer. in International Conference on Artificial Intelligence and Knowledge Processing. 2024. Springer.
Prova, N.N.I. A Novel Weighted Ensemble Model to Classify the Colon Cancer from Histopathological Images. in 2024 International Conference on Computational Intelligence and Network Systems (CINS). 2024. IEEE.
Prova, N.N.I., Enhancing Agricultural Research with an Attention-Based Hybrid Model for Precise Classification of Rice Varieties. Authorea Preprints, 2025.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Well Testing Journal

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This license requires that re-users give credit to the creator. It allows re-users to distribute, remix, adapt, and build upon the material in any medium or format, for noncommercial purposes only.