Automation-Driven Infrastructure Scaling: Enhancing Operational Efficiency in FinTech Cloud Environments

Authors

  • Oreoluwa Omoike

DOI:

https://doi.org/10.38124/ijsrmt.v4i11.953

Keywords:

Automation, Scalability, FinTech Infrastructure, Operational Efficiency, Cloud Computing, Infrastructure-as Code, Digital Resilience

Abstract

The increasing pace of digital transformation in financial technology (FinTech) businesses has further increased the demand for scalable, automated, and resilient infrastructure. With companies moving to cloud-native architecture, automation has emerged as a strategic pillar in attaining elasticity, efficiency, and resiliency in operations in more complex environments. The paper conceptually explores how infrastructure scaling through automation improves the efficiency of operations in FinTech cloud ecosystems. Drawing from the insights of Chowdhary (2025), Gulzar et al. (2024), and Echegu & Agwu (2020) to create a strategic framework of adaptive FinTech operations based on the perspectives of automation, cloud orchestration, and compliance-based scalability. The paper frames automation not as a technical improvement, but as a business ideology that harmonises performance optimisation, regulatory compliance, and service innovation. However, this study elucidates that automation-based scaling can turn FinTech infrastructures into proactive, intelligent networks that can make real-time decisions and predictively maintain themselves by synthesising emerging models, including Infrastructure-as-Code (IaC), Software-Defined Networking (SDN), and continuous integration/deployment (CI/CD). The proposed conceptual model was able to connect technical automation with strategic management principles to provide insights to practitioners aiming to achieve sustainable competitiveness in cloud-enabled FinTech ecosystems.

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Published

2025-11-11

How to Cite

Omoike, O. (2025). Automation-Driven Infrastructure Scaling: Enhancing Operational Efficiency in FinTech Cloud Environments. International Journal of Scientific Research and Modern Technology, 4(11), 9–15. https://doi.org/10.38124/ijsrmt.v4i11.953

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