Making Sense of Regulations with SBVR

The continuous increase in quantity and depth of regulation following the financial crisis has left the financial industry in dire need of making its compliance assessment activities more effective. The field of AI & Law provides models that, despite being fit for the representation of semantics of requirements, do not share the approach favoured by the industry which relies on business vocabularies such as SBVR. This paper presents Mercury, a solution for representing the requirements and vocabulary contained in a regulatory text (or business policy) in a SME-friendly way, for the purpose of determining compliance. Mercury includes a structured language based on SBVR, with a rulebook, containing the regulative and constitutive rules, and a vocabulary, containing the actions and factors that determine a rule's applicability and its legal effect. Mercury includes an XML persistence model and is mapped to an OWL ontology called FIRO, enabling semantic applications.