Regulatory technologies (RegTech) for legal compliance are in high demand in all areas subject to the law, particularly in the financial industry, where the 2008 financial crisis spurred an avalanche of new regulations. This context has promoted the development of RegTech systems to facilitate mining the semantic contents of hundreds of thousands of pages of existing and new legislation. However, an important gap in these systems that hinders their full semantic potential is a lack of functionalities to handle a central element of the meaning of regulations, namely the definitions of terms. For RegTech systems to fully deploy their reasoning power, it is essential that (i) terms appearing in legal documents be well defined from the very start and (ii) the semantics of the definitions be formalised in a machine-understandable format. Yet, definition writing requires uncommon expertise, is time-consuming, costly, and prone to inconsistencies. Similarly, formalising definitions’ semantic contents requires technological expertise that cannot be expected from legal experts. Therefore, there is a need for tools to help legal experts carry out these tasks.

To fill this gap, this applied research project proposes to develop a computer-assisted definition authoring and formalisation system, RegDef. The project aims at (i) changing and enhancing definition writing practices of regulators and legal experts and (ii) enhancing the semantic functionalities of RegTech systems. RegDef will allow regulators in public institutions and legal experts in private companies to craft and edit clear and consistent definitions in legal instruments, such as regulatory documents and smart contracts, while at the same time producing machine-understandable semantic representations of the meaning of relevant terms that can be shared using, for example, semantic web standards. This will ensure that regulatory definitions meet good quality standards and expedite legal experts’ vocabulary building and semantic formalisation tasks, thereby greatly reducing costly human effort.

RegDef is a Marie Skłodowska-Curie Career-FIT research project (MF20180003) co-funded by Enterprise Ireland. The project is carried out at GR3C in the Department of Business Information Systems, University College Cork, Ireland, in partnership with the RegTech company Governor Software. My academic mentor is Professor Tom Butler and my company mentor is Richard Pike.

Career-FIT has received funding from the European Union’s Horizon2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 713654