LangGraph Applications in Finance Training Course

LangGraph Fundamentals for Finance

• A review of LangGraph architecture and stateful execution mechanics.
• Key financial use cases: research copilots, trade support, and customer service agents.
• Considerations for regulatory constraints and auditability.

Financial Data Standards and Ontologies

• Foundations of ISO 20022, FpML, and FIX protocols.
• Strategies for mapping schemas and ontologies into graph states.
• Managing data quality, lineage, and PII compliance.

Workflow Orchestration for Financial Processes

• Designing KYC and AML onboarding workflows.
• Managing trade lifecycles, exceptions, and case handling.
• Structuring credit adjudication and decisioning paths.

Compliance, Risk, and Controls

• Enforcing policies and managing model risk.
• Implementing guardrails, approval chains, and human-in-the-loop interventions.
• Maintaining audit trails, data retention, and explainability.

Integration and Deployment

• Connecting LangGraph to core systems, data lakes, and external APIs.
• Best practices for containerization, secret management, and environment control.
• Establishing CI/CD pipelines, staged rollouts, and canary releases.

Observability and Performance

• Utilizing structured logs, metrics, traces, and cost monitoring tools.
• Conducting load testing, defining SLOs, and managing error budgets.
• Implementing incident response, rollback strategies, and resilience patterns.

Quality, Evaluation, and Safety

• Building unit, scenario, and automated evaluation harnesses.
• Performing red teaming, adversarial prompting, and safety verification.
• Curating datasets, monitoring drift, and driving continuous improvement.

Summary and Next Steps