Explore amol-vishwarupe/EMIR, an open-source Python package with 50 ESMA-style validation rules for EMIR Refit trade reporting. Test compliance faster.
The European Market Infrastructure Regulation (EMIR) Refit transformed derivatives trade reporting across the European Union. According to ESMA, the new reporting requirements took effect on 29 April 2024. Firms must now meet stricter validation rules and data quality standards. But testing those rules is not straightforward. That is where amol-vishwarupe/EMIR enters the picture. It is an open-source Python package designed to help developers and compliance teams validate their EMIR Refit implementation using ESMA-style functional checks.
EMIR Refit is not just a minor update. It introduces a new, stricter trade-reporting regime under EU derivatives regulation. The European Securities and Markets Authority (ESMA) oversees the technical standards behind this framework. The new requirements affect how derivative trades are identified, reported, and validated.
The reporting changes cover more fields, new data formats, and stricter validation logic. Firms must verify legal entity identifiers, derivative product identifiers, and many other data points. The margin for error is small. Rejected reports can lead to regulatory scrutiny and operational inefficiency.
For technology teams, EMIR Refit is therefore a data validation challenge. They need to ensure every report meets the regulatory specification before submission. This requires comprehensive testing and realistic test data.
The complexity of EMIR Refit creates real risk. One wrong field can cause a trade report to be rejected. A rejected report may lead to penalties, especially if it happens repeatedly. Compliance teams need confidence that their systems produce correct reports under all conditions.
Testing is the only way to build that confidence. But regulatory testing is often expensive and slow. Many teams rely on manual checks or vendor tools that are not transparent. That makes it hard to understand why a validation rule failed or what exactly needs to be fixed.
This is where open-source tooling can help. amol-vishwarupe/EMIR provides a reproducible way to test trade-reporting logic. It bundles validation rules, test trades, and reference data into a single package. This makes it easier to integrate regulatory testing into existing development workflows.
amol-vishwarupe/EMIR is a Python-based repository hosted on GitHub. It aims to bridge the gap between regulatory text and software implementation. Instead of reading lengthy regulatory documents, developers can run functional tests that mirror ESMA-style validation rules.
The project is open source. That means anyone can inspect the code, contribute improvements, or adapt it to their own requirements. It also helps smaller firms that do not have large RegTech budgets. With this tool, they can test EMIR Refit compliance without purchasing expensive proprietary software.
The repository includes several key components:
Each component addresses a specific pain point. The validation rules define acceptable data. The test trades show where errors occur. The reference data removes external dependencies. The Claude Code skill demonstrates how AI can accelerate test creation and debugging.
The repository includes 50 validation rules. These are not abstract definitions. They are paired with rule-tagged test trades. This pairing is valuable because it lets developers reproduce validation failures and understand the intent behind each rule.
Each rule maps to a specific test trade. When the test fails, the reason is clear. This helps compliance teams distinguish between code bugs and misunderstood regulatory requirements. It also provides a common language for developers, testers, and compliance officers.
Here is a practical example. Suppose a test trade is configured with an LEI that does not match GLEIF reference data. The validation rule flags the mismatch. The developer can inspect the rule logic and compare it with the ESMA guideline. This closes the loop between regulation and implementation.
The validation rules also act as living documentation. Regulators continue to issue clarifications and updates. Because the rules are open source, they can be adjusted as the regulatory landscape evolves. Teams can add their own cases or modify existing ones without waiting for a vendor release.
A major obstacle in trade-reporting testing is reference data. Verifying a Legal Entity Identifier usually requires access to GLEIF data. Checking a Derivative Product Identifier often requires access to the DSB. These external calls are slow and not always available in development environments.
amol-vishwarupe/EMIR solves this challenge by bundling mock GLEIF and DSB reference data. This lets developers run realistic validation checks without network access or third-party subscriptions. The mock data mirrors the format and structure of real reference data. It is enough to test LEI and DPI validation logic in isolation.
The benefits go beyond convenience. Tests become faster because they do not depend on external APIs. They also become more reliable because network issues cannot cause failures. CI/CD pipelines can run the suite on every commit, catching issues early.
Bundled reference data is also a step toward machine-readable regulation. When reference datasets and validation rules are packaged together, regulatory logic becomes portable. This is a promising direction for the future of compliance testing.
One of the most interesting aspects of amol-vishwarupe/EMIR is the included Claude Code validation skill. This is an emerging pattern in software testing. AI assistants can read rules, generate test cases, and explain failures in plain language.
The skill is designed to support EMIR Refit validation within Claude Code workflows. It helps developers and compliance engineers interact with the rule set more efficiently. Instead of manually tracing through validation logic, they can ask an AI assistant to identify issues and suggest fixes.
Why does this matter? Regulatory testing is repetitive and detail-oriented. AI can reduce the time spent on basic test generation and error interpretation. It can also help onboard new engineers who are unfamiliar with EMIR requirements.
This does not replace human expertise. It augments it. Compliance professionals still need to make the final judgment on complex cases. But tools like Claude Code can handle the routine work and surface insights faster.
For trade-reporting platforms, validation needs to be continuous. EMIR Refit rules are not a one-time checklist. They must be verified whenever code changes, data formats evolve, or reference data is updated. amol-vishwarupe/EMIR is built for this environment.
Because it is a Python package, teams can use it as a standard library or command-line tool. Developers can run the validation rules as part of their build process. If a change breaks a reporting rule, the pipeline fails before the code reaches production.
Here is a simple workflow. After every merge to the main branch, a CI job runs the EMIR validation suite. It checks a set of trade scenarios against the new code. Any failure includes the tagged rule, making debugging direct. This creates a fast feedback loop.
The open-source nature of the package also supports customization. Teams can extend the test cases with their own trade types, reference data, or company-specific rules. This flexibility is indispensable in a fast-moving regulatory environment.
Open-source RegTech tools benefit a wide range of stakeholders. Development teams gain visibility into validation logic. Compliance teams gain reproducible test scenarios. Business leaders gain confidence that reporting systems meet regulatory expectations.
Smaller firms are particularly well served. They may not have a dedicated regulatory technology team. An open-source package gives them a starting point without large license fees. Larger institutions also benefit by using it as a baseline and adding internal controls around it.
The EMIR Refit test package also supports education and training. New analysts can explore rule-tagged test trades to understand how ESMA-style validation works. This is a knowledge resource as much as a testing tool.
The rise of amol-vishwarupe/EMIR reflects several important trends. The first is the growth of RegTech and compliance automation. Between 2024 and 2026, more institutions are expected to invest in automated compliance processes. They want to reduce manual work and improve accuracy.
The second trend is machine-readable regulation. Since EMIR Refit reporting began in April 2024, the industry has moved toward encoding rules in formats that software can consume. Validation rule libraries are a natural fit in this movement.
The third trend is the adoption of AI assistants in software testing and validation. The Claude Code skill bundled with this repository is an early example. As AI tools improve, they will become standard in compliance workflows.
These trends point to a future where regulatory compliance is tightly integrated with software delivery. Open-source projects are likely to play a central role in building shared infrastructure for regulatory validation.
EMIR Refit compliance testing is a serious challenge for any firm involved in EU derivatives markets. amol-vishwarupe/EMIR provides a practical, open-source starting point. It includes 50 ESMA-style validation rules, rule-tagged test trades, and mock GLEIF and DSB reference data. It even offers a Claude Code validation skill for AI-assisted testing.
Whether you are a developer, a compliance officer, or a data engineer, this repository is worth exploring. Integrate it into your CI/CD pipeline. Study the validation rules. Adapt the test scenarios to your needs. Open-source RegTech tools turn complex regulatory requirements into repeatable, automated processes. In a world where regulatory precision matters, that is a clear competitive advantage.
EMIR Refit is the updated EU derivatives trade-reporting regime that took effect on 29 April 2024, introducing stricter validation rules, more fields, and new data formats. Firms must meet these higher data quality standards or risk rejected reports and regulatory scrutiny.
amol-vishwarupe/EMIR is an open-source Python package that provides around 50 ESMA-style validation rules for testing EMIR Refit trade reporting. It helps developers and compliance teams validate their implementation using reproducible functional checks instead of relying only on opaque vendor tools.
Start by cloning the repository and reviewing the documentation to understand the rule set and expected input format. Then install the package dependencies, run the validation suite against your trade reporting data or test files, and use the failure output to fix fields that do not meet the ESMA-style rules.
The main difference is transparency and cost: amol-vishwarupe/EMIR is open source, so you can inspect exactly how each validation rule works and adapt it to your needs without licensing fees. Commercial tools may offer more support, integrations, and official coverage, but they can be less flexible and harder to debug.
Common mistakes include using unrealistic test data, missing key reference data such as LEIs and product identifiers, and not aligning your test cases with the latest ESMA validation rules. It is also easy to overlook the difference between a syntax error and a business-rule failure, so read the validation messages carefully and test edge cases beyond happy-path scenarios.
