Intelligent Serverless Architecture for Real-Time Expense Management: A Function-as-a-Service Approach to Scalable Financial Analytics

Abstract: Effective management of organizational expenditure in distributed computing environments presents persistent challenges, particularly with respect to cost attribution, real-time visibility, and scalable analytics. This paper presents an intelligent, serverless expense management framework built upon Function-as-a-Service (FaaS) paradigms, enabling automated, event-driven financial tracking across multi-tenant cloud deployments. The proposed system integrates a micro services-based backend leveraging AWS Lambda, Azure Functions, or equivalent serverless runtimes with a dynamic, responsive frontend, forming a cohesive full-stack platform for expenditure capture, categorization, and reporting. The architecture incorporates role-based access control (RBAC), multi-dimensional cost aggregation, predictive budget forecasting using lightweight regression models, and RESTful API orchestration through a managed API gateway. Experimental evaluations demonstrate that the proposed framework achieves average API response latencies below 220 ms under concurrent load, reduces infrastructure operational overhead by approximately 63% compared to traditional server-based deployments, and attains a budget-forecasting accuracy of 91.4% measured by mean absolute percentage error (MAPE). The system further supports automated alert generation upon threshold breaches and provides drill-down analytical dashboards for stakeholders. Comparative benchmarking against conventional monolithic and containerized expense systems confirms the superiority of the serverless paradigm in elasticity, cost efficiency, and developer agility. The proposed methodology provides a replicable blueprint for institutions seeking to modernize their financial governance infrastructure through cloud-native technologies.

Keywords: Serverless Computing; Function-as-a-Service; Expense Management; Cloud-Native Architecture; Financial Analytics; Budget Forecasting; Micro services; REST API