Why

SmaRT enables lawyers to semi-automatically process regulations and then express them in a controlled Regulatory Natural Language (RNL), that is both human readable (in Mercury Structured English) and machine readable in XML/RDF/OWL.

Empirical research conducted at the GRCTC in concert with legal firms and major banks in Europe and the US identified a clear need for solutions that enable lawyers or legal and financial subject matter experts to capture, store and transfer/share knowledge of legal and regulatory provisions according to international standards and map these onto the original provisions in a regulatory text. We identified that at base such a solution should also map knowledge of regulatory provisions to business vocabularies and rules in order to enable the drafting of legal advisories, governance policies, procedures and controls to inform regulatory compliance in financial services firms.

Increased Productivity

Human Readable

Machine Computable

SmaRT was designed to provide a real world example of the type of application required by legal or financial SMEs

SmaRT was designed to cumulatively build disambiguated and clarified vocabularies and rules in a regulatory natural language (RNL) that is complete, logical and free of legalese, complexity, and ambiguity, and which is human and machine readable. We have also developed the capability to use a combination of semantic technologies such as our Financial Industry Regulatory Ontology (FIRO) and our standards-based AI & machine learning-enabled NLP tools (Hermes) to identify, extract and load into SmaRT obligations, prohibitions and so on, in a semi-structured format, thereby automating part of this process. Building on these innovations, sophisticated tagging of knowledge in SBVR-compliant Mercury RDF triple stores by the SmaRT application provides powerful capabilities for lawyers to query, extract, transform and load legal and regulatory information for the purpose of enhancing their core value propositions, for internal and external knowledge sharing, for training inexperienced personnel, among several other powerful use cases mentioned above.

In Q4 2017, SmaRT was applied in two highly successful Proofs of Concepts. The first with the RegTech Council in the area of MiFID II Product Governance. The second is with the UK’s Bank of England and the Financial Conduct Authority (FCA) to help make the Handbook both human and machine readable and to have regulatory vocabularies and rules machine executable. Both projects involve global systemically important banks from the US and UK, RegTech vendors, and large legal and professional services firms.

Relationship Correlation

Modality Identification & Classification

Automate Regulation Process

Store Legal Interpretations

Extract Facts and Entities

SmaRT 4 Reg allows lawyers to work faster and be more productive

In sum, SmaRT is a powerful, innovative solution to the Sisyphean problem of regulatory change management in the financial industry and beyond by providing the capability to unpack regulations, systematically and cumulatively in a standardized format that also enables knowledge management in law firms, while enabling straight through regulatory reporting.