Regulatory sequencing

Transforming human readable regulatory text into machine readable form

How we do it

We approach regulation as content, not as code. Because regulation as code is difficult to execute outside of narrow use-cases, since it implies regulatory language is unambiguous. We are sequencing the world’s regulatory information and will make this openly accessible as an innovation platform on which interoperable software applications can be built and that will foster knowledge sharing and creation.

1. Repository

Build a repository of regulatory data.

2. Taxonomy

Domain experts collaborate to build a taxonomy of relevant information covered in the documents.

3. Annotated training dataset

Human experts annotate key information in documents according to the taxonomy, ultimately building an annotated training dataset.

4. Classifier model

Annotated documents are used to train a classifier model using AI/ML.

5. API

Trained classifiers machine-sequence regulatory documents, with sequenced data output to an API.

6. Applications

Interoperable applications access the machine readable data through the API.

Machine-readable regulation: an introduction

Emmanuel Schizas, Head of Product at Regulatory Genome Project and Lead in Regulation and RegTech at Cambridge Centre for Alternative Finance, Cambridge Judge Business School, offering an intro on our approach to machine-readable regulations.

Join our team

If you enjoy working in a dynamic, collaborative environment where new ideas and creativity are always encouraged, view our open positions.

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