A case study on modeling and validating financial regulations using (semi-) automated compliance framework

Abstract

Modern enterprises operate in an unprecedented regulatory environment where increasing regulation and heavy penalties on non-compliance have placed regulatory compliance among the topmost concerns of enterprises worldwide. Previous research in the field of compliance has established that the manual specification/tagging of the regulations not only fails to ensure their proper coverage but also negatively affects the turnaround time both in proving and maintaining the compliance. Our contribution in this paper is a case study using a subset of European Union Regulation in the financial markets, namely, Money Market Statistical Reporting (MMSR) and that we validated it in the context of our model-driven semi-automated compliance framework. The novelty of the framework is the key participation of domain experts to author regulatory rules in a controlled natural language to enable compliance checking. We demonstrate transformation of regulations present in legal natural language text (English) to a model form via authoring of Structured English rules in the context of MMSR regulations for a large European bank. This generated regulatory model is eventually translated to formal logic that enables formal compliance checking contrary to current industry practice, that provides content management-based, document-driven and expert-dependent ways of managing regulatory compliance.