Agentic and Generative AI for Real-Time Financial Process Automation in Cloud-Native DevOps Environments

Abstract

Real-time automation of financial activities, including approvals, controls, routing, and monitoring, can enable fast response to opportunities and threats, eliminating the rotation of capital through liquidity provider balances and streamlining interactions with sources of capital. Generative and agentic AI technologies, supported by real-time data streams of events, market feeds, and key risk indicators, can automate and govern these transactions provided that high standards of latency, throughput, security, and regulatory compliance are achieved. A cloud-native DevOps ecosystem equipped with serverless infrastructure-as-code patterns ensures scalable, cost-effective operations with minimum user interference, allowing a comprehensive evaluation of operational performance, change management, security controls, and regulatory oversight. Scenarios involving AI agents as the driving or supervisory part of automation workflows illustrate the architectural paradigm. The analysis identifies the expected challenges in operational responsibility and response reliability, gathering additional evidence from existing Cloud-Native/Serverless solutions of similar scope. Mitigation strategies address the main issues encountered in every-day AI adoption and propose supporting operations management and security controls. The examination of the full end-to-end process flow, including off-line and real-time phases, ensures cover for Governance, Risk, and Compliance (GRC) objectives by design and the definition of a robust plan for evaluation in on-line use.