Building Scalable Batch Processing Systems for Financial Transactions Using Mainframes - Gill, Akash (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2019)
Using mainframes to develop highly scalable batch-processing systems for financial transactions is mandatory for banking solutions with a high transaction rate. In this article, the author focuses on the role of Mainframes in making financial systems effective, scalable, and robust. One of the technologies widely used in financial institutions is batch processing, which helps institutions to complete large volumes of data processing at low costs, bearing high costs on both hardware and human resources to complete the transactions. The article is more of a technical nature, exploring the principles of building and deploying large and extendible batch processing environments with an emphasis on using COBOL for program development, JCL for scheduling, and DB2 for integration. In this regard, the principal approaches include job prioritization, load balancing, and error recovery measures, all discussed to improve performance and reduce downtime. The result of deploying such systems consists of minimizing the time it takes to complete the various transactions and adapting to the expanding needs at the corporate level. Mainframe technology has user-friendly functions and capabilities that are suitable for today’s financial institutions because these institutions require systems that provide services to customers effectively and safely with extensive scalability. Therefore, it is essential to point out from this article that Mainframes remain critical infrastructure in the move to digital financial services.