Enhancing Enterprise Financial Management through Mobile Edge Computing: A Real-Time Financial Analysis Approach

Abstract

In an era of rapid digital transformation, enterprises require agile and intelligent financial management solutions to ensure real-time decision-making and operational efficiency. Mobile Edge Computing (MEC) offers a decentralized computing paradigm that brings data processing closer to the source, minimizing latency and enhancing computational efficiency. This paper explores the integration of MEC into enterprise financial management to enable real-time financial analysis, risk assessment, and decision support. By leveraging MEC’s low-latency processing capabilities, businesses can enhance financial forecasting, fraud detection, and resource allocation with unprecedented speed and accuracy. The proposed framework incorporates cloud-edge collaboration, AI-driven analytics, and secure data transmission to optimize financial workflows while maintaining data integrity and compliance. Through case studies and experimental results, we demonstrate the efficacy of MEC in streamlining enterprise financial operations. This study highlights the transformative potential of MEC in reshaping financial management strategies, providing enterprises with a competitive edge in a data-driven economy.