Research: Autonomous Cognitive Agents for Financial Enterprise Orchestration: A Generative Framework for Intelligent Workflow Automation in Banking Systems
The digital infrastructure of modern financial institutions relies on enterprise resource planning systems constrained by static, rules-based architectures ill-suited for contemporary financial operations. This paper introduces a paradigm for financial process automation through autonomous cognitive agents capable of dynamic workflow orchestration across banking systems. The proposed framework integrates large language model reasoning with modular agent coordination to enable end-to-end execution of complex financial tasks including interbank settlement, regulatory compliance verification, and transactional processing. Through a structured event representation schema that transforms raw financial logs into semantically rich decision sequences, the system achieves contextual understanding previously unattainable with conventional automation. Empirical validation within operational banking environments demonstrates significant performance improvements across wire transfer processing and employee reimbursement management. Results indicate processing time reductions of up to 40% for wire transfers and 82% for reimbursement cycles, accompanied by error rate decreases exceeding 94% through automated validation against regulatory and policy frameworks. The architecture introduces parallel execution of compliance checks, real-time risk assessment, and intelligent task decomposition that collectively enhance both operational efficiency and regulatory adherence. By establishing a foundation for AI-native financial infrastructure, this work addresses fundamental limitations of legacy banking systems while charting a path toward autonomous, interpretable, and compliant financial process execution.