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@article{192287,
        author = {INDRAJEET SANAS and NAITIK MENGADE and SURAJ RAKSHE and MAHESHKUMAR MORE},
        title = {Foreign Exchange Plaza: A Microservices-Based Currency Exchange : Currency conversion, redefined by Microservices.},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {9},
        pages = {913-923},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=192287},
        abstract = {With the rapid expansion of the global digital economy, there is a growing requirement for currency exchange platforms that can operate efficiently while maintaining security, scalability, and reliability. Many existing currency exchange systems are developed using traditional monolithic architectures, which often struggle to satisfy modern user expectations such as real-time exchange rate access, fast transaction processing, and personalized financial services. Limitations such as high latency, restricted scalability, and difficulty in upgrading individual components reduce the overall effectiveness of such systems.
This paper presents Foreign Exchange Plaza, a microservices-based currency exchange platform designed to address these challenges by adopting a modular and distributed system architecture. The proposed system divides complex functionality into independently deployable microservices, where each service is responsible for a specific operation such as exchange rate aggregation, transaction orchestration, fraud detection, user profiling, and predictive analytics. This architectural approach improves fault isolation, system scalability, and ease of maintenance.
The platform is implemented using containerized services deployed over a Kubernetes environment to ensure high availability, horizontal scalability, and fault tolerance. An API Gateway is employed as a unified access point to manage authentication, request routing, and rate limiting. Real-time exchange rates are collected from multiple trusted financial data providers, normalized into a standard format, and cached to support fast response times. The transaction processing module ensures consistency and atomic execution across distributed services. A fraud detection mechanism based on machine learning techniques is integrated to identify abnormal transaction patterns using parameters such as transaction frequency, device information, and geolocation data.
Additionally, the system incorporates a predictive analytics engine that utilizes time-series forecasting models to analyze historical data and market trends. This enables the platform to provide users with insights such as optimal transaction windows and recommended currency pairs. User interaction data is continuously analyzed to personalize dashboards and improve overall engagement. UML-based system modeling, including use case and activity diagrams, is used to represent interactions among users, administrators, and compliance authorities. Experimental evaluation indicates improvements in transaction throughput, reduced response
atency, and high user satisfaction levels. The modular design of Foreign Exchange Plaza allows future integration of advanced features such as blockchain-based transaction logging, AI- assisted trading support, and multilingual user interfaces, making it adaptable to evolving financial and regulatory requirements.},
        keywords = {Microservices Architecture, Currency Exchange Architecture, Real-Time Rate Aggregation, Transaction Orchestration, Fraud Detection, Predictive Analytics, API Gateway, Containerization, Financial Compliance, User Personalization.},
        month = {February},
        }