LangGraph Applications in Finance Training Course

LangGraph Basics for the Financial Sector

• Overview of LangGraph architecture and stateful execution principles.
• Financial use cases: research copilots, trade support, and customer service agents.
• Considerations regarding regulatory constraints and auditability.

Financial Data Standards and Ontologies

• Fundamentals of ISO 20022, FpML, and FIX.
• Integrating schemas and ontologies into graph states.
• Managing data quality, lineage, and PII.

Orchestrating Workflows for Financial Processes

• Workflows for KYC and AML onboarding.
• Trade lifecycle management, exception handling, and case management.
• Credit adjudication and decision-making paths.

Compliance, Risk Management, and Controls

• Policy enforcement and model risk management strategies.
• Implementing guardrails, approvals, and human-in-the-loop steps.
• Ensuring audit trails, data retention, and explainability.

Integration and Deployment Strategies

• Connecting to core systems, data lakes, and APIs.
• Managing containerization, secrets, and environments.
• Establishing CI/CD pipelines, staged rollouts, and canary releases.

Observability and Performance Optimization

• Monitoring structured logs, metrics, traces, and costs.
• Load testing, defining SLOs, and managing error budgets.
• Incident response, rollback procedures, and resilience patterns.

Quality Assurance, Evaluation, and Safety

• Utilizing unit, scenario, and automated evaluation harnesses.
• Red teaming, adversarial prompts, and safety verification.
• Dataset curation, drift monitoring, and continuous improvement.

Conclusion and Future Steps