Global Trustee and Fiduciary Services News and Views Issue 50

Prime, Futures and Securities Services | Financial Innovation 60 Figure 1 indicates the role regtech can play in automating regulatory compliance reporting. The context of various elements of this ground-breaking activity are now described. The FCA currently publishes its Handbook of Regulations in the World Wide Web Consortium’s (W3C) HTML and in PDF. Key concepts are linked using hypertext protocol. In the FCA’s case, specific concepts are defined in the Handbook Glossary. The move to digital regulation and regulatory reporting and to digital regulatory compliance, based on standards such as Semantics of Business Vocabulary and Rules (SBVR) and the W3C Semantic Stack, is a significant paradigm shift. In figure 1, regtech vendor RegDelta demonstrated how its taxonomies of regulatory topics using the W3C’s Simple Knowledge Organisation System (SKOS) and AI could be used to semantically tag regulatory provisions to indicate their scope and application. SKOS is based on the W3C’s Resource Description Framework (RDF), and is one of the three foundational Semantic Web technologies, the other two being the SPARQL Protocol and RDF Query Language (SPARQL) and the Web Ontology Language (OWL). RDF is the data-modelling language for semantic technologies. It captures the relationships between concepts in triples (e.g. investments firm manufactures financial products ). In figure 2, a RAG3 firm must submit FSA001 is captured as an RDF triple. There are several serialisations of RDF, such as Turtle (Terse RDF Triple Language, which is less verbose and easier to use than RDF) and TriG, while JSON-LD brings RDF to the Java world. The semantic tagging of regulations is but the first step in the regulatory compliance process and the SKOS namespace (e.g. the machine- readable syntax for building vocabularies) helps address the Tower of Babel problem. This is an example of the straightforward application of AI and semantic technologies to help manage the volume and complexity of regulations by having a machine answer “what” and “which” questions, i.e. what are the themes in regulatory provisions and which activities and products do they target. Figure 1 An applied model of digital regulatory compliance Taxonomies Machine Executable Regulatory Reports Firm Data Legal Firms Regulatory Knowledge Base SmaRT ® Interpret Disambiguate Stylize Clarify Store Governance RegTech Regulatory Alerts Human & Machine Readable Rules Regulatory Tagging using RegDelta ® taxonomies Linked Knowledge in RDF OWL Regulations Model DR ® ontologies Legal Compliance IT Business Model Knowledge Base SKOS Vocabulary NLP Software Enterprise Databases SPARQL REGnosys ® automated compliance monitoring XBRL ® taxonomies Firm Knowledge Base HTML Regulatory Report XBRL ® taxonomies XML PDF