The high rate of digital payment systems expansion has raised the need to realize high-performing and scalable transaction processing circuits in FinTech applications. Conventional systems use a main queuing structure based on the First-In-First-Out (FIFO) model and this type of structure can be associated with delays due to huge numbers of transactions that have to be processed and this is usually the case during peak hours. The paper will provide a design and implementation of an effective transaction processing system based on Java-based data structures. The suggested system incorporates Queue as a standard processing, Priority Queue as a high-priority transaction processing mechanism and HashMap to retrieve account information efficiently. This mixed solution will provide expedited handling of urgent transactions and equity to routine traffic. Light weight simulation is run to compare the traditional queue based processing with priority based scheduling. The findings are better efficiency and lower latency of transaction processing. The suggested system shows that optimal data structures can improve the performance and scalability of contemporary digital payment systems.