Glossary

Data governance refers to the framework of standards, processes, and responsibilities that ensure an organization’s data is accurate, secure, traceable, and consistently managed. For finance teams, it forms the backbone of every critical workflow, from bank reconciliation and supplier billing control to financial reporting and audit readiness.

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A strong governance framework typically includes:

• Clear data ownership to preserve quality and accountability
• Role-based access control to protect sensitive financial information
• Standardization rules that keep data consistent across entities and systems
• Security and compliance policies, including GDPR and retention rules
• End-to-end traceability for audit visibility and risk reduction

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In an AI-powered finance environment, data governance is not optional, it determines whether automation is reliable, compliant, and scalable. AI agents require structured, trustworthy inputs; without governance, errors propagate faster, compliance risks increase, and financial decisions become less reliable.

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Phacet embeds governance directly into every workflow. Each AI agent operates with source-linked citations, permission layers, human-in-the-loop validation, and full auditability, ensuring teams retain control even when automation handles thousands of documents or transactions per day. This governance-by-design approach allows finance teams to automate confidently while maintaining high standards of accuracy and compliance.

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To explore how Phacet applies governance principles in real-world workflows, see the Contract Intelligence use case, which illustrates how structured extraction, traceability, and supervised AI reinforce data reliability at scale.