Building a scalable enterprise data architecture for financial institutions

Kallem, Bharat Kumar Reddy (2025) Building a scalable enterprise data architecture for financial institutions. World Journal of Advanced Engineering Technology and Sciences, 15 (1). pp. 1153-1157. ISSN 2582-8266

Enterprise data architecture for financial institutions has evolved dramatically to address the exponential growth of financial data, which now exceeds 2.5 exabytes daily with a 40% annual growth rate. Traditional infrastructures struggle to meet modern operational demands, with a significant majority of institutions reporting scaling challenges. The shift toward real-time processing requirements compounds these difficulties as banking systems process billions of transactions daily while investment platforms handle hundreds of thousands of market data messages per second during volatility events. Modern architectural approaches include multi-tiered storage systems, domain-oriented data meshes, cloud-native deployments, and comprehensive governance frameworks that deliver substantial improvements across performance, integration, scalability, and security dimensions. Organizations implementing these advanced architectures experience dramatic reductions in processing latency, significant improvements in cross-domain analytics, enhanced deployment frequency, and strengthened security postures. These architectural transformations yield measurable business outcomes, including improved customer satisfaction, enhanced risk detection capabilities, reduced infrastructure costs, and accelerated time-to-market for financial products and services