Operational analytics in financial services: Enabling real-time decisions and strategic agility

Dubey, Harshita (2025) Operational analytics in financial services: Enabling real-time decisions and strategic agility. World Journal of Advanced Engineering Technology and Sciences, 15 (3). pp. 1727-1765. ISSN 2582-8266

Operational analytics has transformed financial services, evolving from a support function to a strategic asset driving competitive advantage. This evolution enables real-time decision-making capabilities across multiple domains including risk management, customer experience enhancement, compliance, and operational efficiency. Through sophisticated monitoring infrastructures and machine learning algorithms, financial institutions can detect fraud patterns, optimize risk positions, and respond dynamically to market conditions. Analytics-driven customer journey mapping eliminates friction points while enabling hyper-personalized experiences that adapt to individual preferences and contextual factors. In compliance operations, analytics facilitates continuous oversight through pattern recognition and behavioral baseline analysis while enhancing PII protection through dynamic security frameworks. Operational efficiency benefits from process mining techniques that visualize actual workflows, service provisioning optimization through digital twins and queue modeling, and reliability improvements via predictive maintenance and automated root cause analysis. The integration of cloud computing, artificial intelligence, and stream processing technologies has accelerated these capabilities, enabling unprecedented speed and scale in extracting actionable intelligence from vast volumes of financial data. Financial institutions leveraging these capabilities demonstrate superior performance across key metrics including customer satisfaction, operational efficiency, and regulatory compliance.