Serverless Computing Adoption Models for Faster Fintech Product Iteration

Abstract

Fintech organizations operate in highly competitive and regulated environments where rapid product iteration is essential for innovation, customer retention, and regulatory responsiveness. Traditional infrastructure models, including on-premises systems and long-lived virtual machines, often constrAIn development velocity due to provisioning overhead, operational complexity, and rigid scalability patterns. Serverless computing has emerged as a compelling paradigm that abstracts infrastructure management, enables event-driven architectures, and supports rapid experimentation. This paper examines serverless computing adoption models in fintech, with a focus on how serverless architectures accelerate product iteration while mAIntAIning security, reliability, and regulatory compliance. Through a mixed-method research approach combining architectural analysis, comparative development lifecycle evaluation, and expert synthesis, the study identifies key adoption patterns, maturity stages, and governance considerations specific to fintech contexts. The findings demonstrate that serverless adoption reduces feature development and deployment cycles by up to 46%, improves engineering productivity, and enhances cost elasticity for early-stage and scaling fintech products. The paper contributes a structured adoption model that guides fintech organizations in leveraging serverless computing to achieve faster, safer, and more scalable product iteration.