Migrating Legacy Systems to Cloud-Native Architectures for Enhanced Fraud Detection in Fintech
DOI:
https://doi.org/10.53555/ephijse.v9i1.236Keywords:
Legacy systems, cloud-native architectures, fraud detection, CI/CD, Anomaly detectionAbstract
In the ever-evolving fintech landscape, the need for robust fraud detection mechanisms and real-time monitoring has become paramount. Legacy systems, often hindered by outdated infrastructure and limited scalability, pose significant challenges in meeting these modern requirements. This paper explores strategies and best practices for migrating legacy fintech systems to cloud-native architectures, with a focus on enhancing fraud detection capabilities. Migrating to cloud-native environments offers numerous advantages, including scalability, flexibility, and advanced analytics, which are crucial for effective fraud detection. This process involves several critical steps: assessing the current system, identifying the components that need modernization, and
planning the migration to minimize downtime and data loss. Key strategies include containerization, microservices adoption, and leveraging managed cloud services for data processing and analysis. A significant aspect of this migration is the
implementation of real-time monitoring and analytics. Cloud-native solutions enable the integration of machine learning and artificial intelligence to detect and respond to fraudulent activities swiftly. Best practices include setting up continuous integration and continuous deployment (CI/CD) pipelines, automating security checks, and employing a zero-trust security model to safeguard sensitive financial data. This paper aims to provide a comprehensive guide for fintech organizations looking to modernize their systems. By adopting cloud-native architectures, these organizations can not only enhance their fraud detection capabilities but also achieve greater operational efficiency and resilience. Through real-world examples and practical insights, we illustrate the transformative impact of this migration on the fintech industry's ability to combat fraud in a dynamic digital environment.
References
Wewege, L., Lee, J., & Thomsett, M. C. (2020). Disruptions and digital banking trends. Journal of Applied Finance and Banking, 10(6), 15-56.
Zaballos, A. G., & Rodriguez, E. I. (2018). Cloud Computing: Opportunities and Challenges for Sustainable Economic Development in Latin America and the Caribbean.
Remolina, N. (2019). Open banking: Regulatory challenges for a new form of financial intermediation in a data-driven world.
Mei, L. (2022). Fintech Fundamentals: Big Data/Cloud Computing/Digital Economy. Mercury Learning and Information.
Mallidi, R. K., Sharma, M., & Vangala, S. R. (2022, August). Streaming Platform Implementation in Banking and Financial Systems. In 2022 2nd Asian Conference on Innovation in Technology (ASIANCON) (pp. 1-6). IEEE.
Pal, P. (2022). The adoption of waves of digital technology as antecedents of digital transformation by financial services institutions. Journal of Digital Banking, 7(1), 70-91.
Chishti, S., & Barberis, J. (2016). The Fintech book: The financial technology handbook for investors, entrepreneurs and visionaries. John Wiley & Sons.
Gupta, P., & Tham, T. M. (2018). Fintech: the new DNA of financial services. Walter de Gruyter GmbH & Co KG.
Castejón Teruel, A. (2018). The rise of FinTech in the global financial markets.
Das, S. R. (2019). The future of fintech. Financial Management, 48(4), 981-1007.
Arslanian, H., & Fischer, F. (2019). The future of finance: The impact of FinTech, AI, and crypto on financial services. Springer.
Suryono, R. R., Budi, I., & Purwandari, B. (2020). Challenges and trends of financial technology (Fintech): a systematic literature review. Information, 11(12), 590.
Ofir, M., & Sadeh, I. (2021). The Rise of FinTech: Promises, Perils, and Challenges. Perils, and Challenges (February 18, 2021).
Lu, H., Wu, Q., & Ye, J. (2020). Fintech and the future of financial service: A literature review and research agenda.
Sarhan, H. (2020). Fintech: an overview. ResearchGate: Berlin, Germany, 1-34.