Driven by the wave of digital reform in the financial field, traditional monolithic architectures have exposed problems of limited performance and flexibility. As an innovative system architecture pattern, microservices have become a key choice for optimizing system performance in the financial industry due to their excellent scalability, flexibility, and independence. This article focuses on the characteristics of microservices and conducts in-depth research on their practical applications in the financial field, with a particular emphasis on their specific applications in payment processing, risk control, and customer service. Further performance evaluation was conducted on the efficient microservice architecture, and optimization paths were studied in handling high concurrency requests, ensuring data consistency, executing transaction processing, and system fault tolerance. The research results show that microservice architecture has demonstrated significant advantages in accelerating system response speed, reducing processing latency, and improving system availability, providing strong technical support for the smooth operation of the financial industry.

Jin Li. Performance Analysis of Efficient Microservice Architecture in the Financial Industry. Machine Learning Theory and Practice (2026), Vol. 6, Issue 1: 1-9. https://doi.org/10.38007/ML.2026.060101.

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