followthemoney

What it is and what it does

followthemoney is a data model and toolkit designed for investigators, journalists, and compliance researchers working with financial crime and anti-corruption data. Rather than aiming for an ideal theoretical model, it prioritizes practical usability by simplifying complex legal concepts into a working structure for efficient data processing. The package defines schemas for common entities (people, companies, assets, payments, ownership relations, court cases) and provides validation and normalization code to ensure data quality.

Beyond the schema itself, followthemoney includes a command-line tool for processing and transforming data, mapping from tabular formats into the model, and generating RDF/OWL representations. It integrates with established libraries like SQLAlchemy, Pydantic, RDFlib, and NetworkX to support both relational and graph-based workflows. The project maintains active documentation and an explorer for schema definitions, making it suitable for teams building investigative data pipelines.

Use it for:

• Build a database of corporate ownership networks and beneficial ownership chains for anti-corruption investigations.
• Normalize and validate entity records (names, addresses, identifiers) from multiple sources before merging into a single dataset.
• Transform spreadsheet or CSV data into a standardized entity-relationship model for compliance reporting.
• Generate RDF/OWL exports of financial crime data for semantic web tools and linked-data applications.
• Map court case records, sanctions lists, and payment flows into a unified schema for cross-domain analysis.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Provides a pragmatic data model and validation toolkit for entities in investigative reporting and financial crime research—people, companies, assets, payments, ownership relations, court cases—with CLI tools for data transformation and mapping.

Yes. followthemoney is actively maintained, has no known vulnerabilities, and solves a specific and well-defined problem for investigative and compliance workflows. The permissive MIT license poses no restrictions. Install friction is low and dependencies are mature. It is worth installing if you are building a data pipeline for financial crime, sanctions, or investigative journalism work.

Install

followthemoney on PyPI

pip install followthemoney

uv add followthemoney

poetry add followthemoney

Installing followthemoney

Before you install

Low friction install with a wheel distribution. Active maintenance with recent releases; 17 runtime dependencies are substantial but well-established libraries (pydantic, sqlalchemy, rdflib, networkx). Requires Python 3.11+.

License in practice

MIT License (permissive). You may use, modify, and distribute this package freely in commercial and private projects, provided you include the license notice and copyright attribution to Journalism Development Network, Inc. and OpenSanctions Datenbanken GmbH.

Quickstart

pip install followthemoney

from followthemoney import model

# Access the schema
schema = model.get('Person')
print(schema.label)

Requires Python 3.11 or later. The description notes that pyicu (a text-processing dependency) can be tricky to install on some systems; review its documentation if installation fails.

Verify before relying

• Whether pyicu is included in the standard install or requires separate setup steps on all platforms.
• Performance characteristics when processing large datasets or complex ownership networks.
• Compatibility with downstream tools that consume followthemoney-modeled data.

Package facts

Evidence: followthemoney-4.10.1-py3-none-any.whl

Tags

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Further reading