Agentic Use Cases
A production-grade governance checklist for multi-agent banking systems under CBUAE's AI principles. Use this before every production deployment cycle.
Based on hands-on experience building agentic AI across fintech and regulated banking environments. A companion production governance playbook is available on request.
CBUAE's Five Governance Principles
Every agentic system must be evaluated against these five dimensions before production deployment.
Fairness
No discriminatory outcomes across protected attributes
- Audit training data for representation gaps before model deployment
- Test outputs across demographic segments for disparate impact
- Document mitigation strategies for identified biases
- Review fairness metrics quarterly and after any retraining
Transparency
Explainable decisions and auditable reasoning chains
- Publish model cards documenting purpose, limitations, and performance
- Log chain-of-thought reasoning for every agentic decision
- Provide structured explanations to users and auditors on demand
- Disclose when an AI system is interacting with or deciding on behalf of a customer
Accountability
Clear ownership for every agentic action and escalation
- Assign a named accountable owner for each agentic workflow
- Define escalation paths from automated to human decision-making
- Maintain immutable audit trails with timestamps and actor identities
- Establish clear liability frameworks for model failures or errors
Data Governance
Classification, retention, and access control for training and inference data
- Classify all data by sensitivity level before ingestion into agentic systems
- Implement role-based access controls with least-privilege principles
- Define data retention periods aligned with regulatory requirements
- Monitor for data leakage in agent outputs and intermediate reasoning
Human Oversight
Meaningful human review at every critical decision point
- Identify high-stakes decisions requiring mandatory human approval
- Design override mechanisms that allow humans to reject agent recommendations
- Train operators on model capabilities, limitations, and failure modes
- Log all human interventions and their outcomes for continuous improvement
Pre-Deployment Checklist
Three pillars of production-ready agentic governance. Complete every item before going live.
Model Inventory & Regulatory Mapping
Map every agentic use case to CBUAE's five governance principles: fairness, transparency, accountability, data governance, and human oversight.
Retrieval & Agent Coordination Metrics
Measure what matters in multi-agent systems — precision, escalation accuracy, and approval chain integrity — not just latency.
Third-Party LLM Risk Register
Maintain a living register for every external model API with model cards, red-team evidence, and breach SLAs.
Production Governance Playbook
I have a comprehensive playbook for multi-agent banking systems under similar regulatory frameworks. It covers model inventory templates, retrieval evaluation frameworks, third-party risk registers, approval chain designs, and incident response playbooks — everything needed to operationalize the checklist above.
Related Frameworks
Deeper resources for building trustworthy agentic systems.