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LEI Governance Graph Agent with LangChain & LangGraph

Unowned and stale Legal Entity Identifier (LEI) records create critical blind spots in financial counterparty identification and trade reporting. Build an LEI portfolio governance agent using LangChain and LangGraph to track entity ownership changes, evaluate registration drift, and flag orphan records with 95% accuracy across global LEI datasets.

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What you are building

Build a stateful, graph-based governance tracking workflow using LangChain and LangGraph to detect orphaned and stale LEI portfolios.

How work is evaluated

Evaluation

Evaluates orphan LEI identification accuracy and correctness of state graph transitions.

Datasets

Public datasets, plus the private datasets you have access to.

How submissions are scored

Dimensions
2 scoring checks
Binary
2 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1

graph_execution_success

Verifies that the LangGraph workflow completed without state execution errors.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 2

orphan_detection_accuracy

Accuracy of identifying unowned and lapsed LEI records. • target: 0.95 • range: 0-1

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

  • Design stateful LangGraph node workflows representing entity lifecycle stages

  • Construct LangChain tool interfaces to query GLEIF open APIs and registry databases

  • Detect unassigned, expired, or orphaned LEI records across institutional portfolios

  • Generate automated compliance remediation tickets for institutional ops teams

Resources

Dataset notes

Synthetic portfolio of 500 LEI records representing diverse status types (ISSUED, LAPSED, MERGED, RETIRED) across global asset managers.

Challenge setup

Evaluates orphan LEI identification accuracy and correctness of state graph transitions.

Challenge input

JSON array of corporate LEI records containing registration status and renewal date

LangChain

Framework for building chains and tool integration.

LangGraph

Stateful workflow orchestration engine for complex decision graphs.

Evaluated output

JSON governance status report detailing orphan_count, lapsed_count, and actions_required

Evaluation checks
  • Verifies that the LangGraph workflow completed without state execution errors.
  • Accuracy of identifying unowned and lapsed LEI records. • target: 0.95 • range: 0-1
Configured evaluation evidence
  • Benchmark: LEIGovernance-Bench-v1
  • Orphan Detection Accuracy target: 0.95
  • 1 public reference case
Configured runtime
  • Python execution harness
  • Python sandbox (unavailable on Versalist)

Shows the first task, up to three tools, and up to three evidence items.

View technical recipe

Configured tools

Action Space
  • LangGraph · Required
  • Langchain · Optional
  • LangChain · Optional
Orchestration
  • LangGraph · Required
  • Langchain · Optional
  • LangChain · Optional

Evaluation contract

  • graph_execution_success · Weight 1
  • orphan_detection_accuracy · Weight 1

Metrics

  • orphan_detection_accuracy · Target 0.95

Benchmarks

  • LEIGovernance-Bench-v1
  • security

Reference cases

  • 1 public reference case

Workflow tasks

  1. Task 1

    Input: JSON array of corporate LEI records containing registration status and renewal date

    Output: JSON governance status report detailing orphan_count, lapsed_count, and actions_required

    Execution harness: Python

Evaluation tools

  • LangChain · Agent Framework
  • LangGraph · Graph Orchestration Framework

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about LEI Governance Graph Agent with LangChain & LangGraph