Generative AI for Secure Real-Time Financial Transaction Governance in the Cloud
Keywords:
Generative Artificial Intelligence in Financial Governance, Augmented Governance by Design, Real-Time Secure Transaction Processing, Cloud-Based Financial Ecosystems, AI-Driven Policy and Compliance Automation, Governance Decision Proposal Frameworks, Risk–Control–Accountability Integration, Explainable and Auditable AI Systems, Transparency in Financial Decision-Making, Trust-Centric AI Architectures, Provenance-Enriched Data Pipelines, Compliance-Aware AI Deployment, Secure Cloud Governance Models, RegTech-Enabled Financial Oversight, AI-Supported Enterprise Risk Management.Abstract
Financial governance may benefit from generative AI as it promotes augmented governance by design. The resulting capability is operationalized as a blueprint for real-time secure transaction processing in cloud ecosystems. Through the design and integration of the various system layers, desired characteristics of transparency, explainability, auditability, and trust become built-in features that support and enhance the risk management, control, and decision-making processes of stakeholders across the value network by providing and assuring consistent information, even in the presence of uncertainty.
Generative AI is applied to define the decision-making process, specifying how the Generative AI Governance Decision Proposal defines financial policy and compliance. Consequently, the related sense—analyze—respond model of augmented governance identifies the roles, responsibilities, decision rights, escalation paths, and governance rituals that provide the operational framework for governance. Data ingestion pipelines enrich the provenance of information to support enhanced risk–control–accountability. Transparency is specified from a governance perspective, defining policy alignment for trust in the AI–enabled financial decision outcomes.
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