In our previous post about the RegTech world we focused on how the improvement of the regulatory data quality can positively affect the GDP growth of a country. This statement is present within the pages of the “RegTech for Regulators” report by the World Government Summit, which in fact has been the main focus of our latest blog post. It is now time to address our review to another part of the “RegTech for Regulators” paper, namely the one dedicated to the "Regulation as a Platform" model, which is quite close to the "RegTech as a Service" one, which we defined in another post. These two concepts reflect in the best way what we are doing at Aptus.AI with our proprietary Artificial Intelligence technology for the generation of machine readable regulations, so it is worth to go deeper into them.
The expression Regulation as a Platform identifies "a holistic approach in which regulators collaborate with businesses, government entities and citizens to drive innovation and improve compliance outcomes". Well, the AI-powered machine readable regulations exploited in Daitomic are exactly thought to "use advanced capabilities such as Machine Learning and analytics to make it easier for business and government to understand and work with regulation". The example mentioned in the paper is the prototype of Regulation as a Platform developed in Australia by Data61, which is a part of the Commonwealth Scientific and Industrial Research Organization. This proof-of-concept project provides "free and open access to legislation and regulation via public APIs, which will allow users to access the database of endorsed logic rules and a reasoning engine to process rules and data into accessible digital logic". The work of Data61 team is quite similar to the one we’re carrying on at Aptus.AI, as they use Natural Language Processing to scan the regulatory text and to ensure right interpretation and development of regulatory logic, which is coded into a single API with the aim to cover all government legislation. The workflow includes the conversion of rules into digital logic, the oversight by policy experts and regulators to ensure that the digital logics represent oversight of the intent of the law. Then, after the quality checking, the regulatory documents are endorsed for publication by regulators and made publicly available on the Regulation as a Platform prototype.
As written in the paper, "the emergence of digital legislation and regulation as a platform opens up avenues for the creation of innovative advisory applications for both regulators and business" by adding “to this existing infrastructure is machine readable legislation as a new data feed". The combination of the Regulation as a Platform model with the already existing data and analytics can promote the development of innovative Risk Management platforms, just like Daitomic. This solution, in fact, helps compliance professionals make better decisions, leading to improved outcomes for all stakeholders. In particular, the benefits for organizations arising from such technologies can be identified in three types:
This presentation of the Regulation as a Platform model clearly expresses why "RegTech offers a significant opportunity for regulators and regulated entities to improve compliance, reduce costs and promote innovations". Exploiting these tools, regulators "can unlock the wealth of data and information [...] to better monitor risks, improve their supervisory role and introduce business process efficiency". These new approaches can be tested through a "cloud-based infrastructure and Regulatory Sandboxes implemented in collaboration with the industry" in order to "move towards machine readable regulations for greater consistency and improved compliance". Well, at this point it should be clear why this paper by the World Government Summit in collaboration with Accenture represents another confirmation of the work we are doing in Aptus.AI with Daitomic and in the context of the Fintech Milano Hub. We are aware for a while that "converting regulatory text to machine readable format using Natural Language Processing and semantic language models - which we present in this post - can help narrow the gap between regulatory intent and interpretation", thus exploiting the Regulation as a Platform model to provide "free and open access to legislation and regulation, making it easier for businesses to understand and comply with regulations". All this theory, actually, is already embodied in the AI technology at the core of Daitomic. And it is also already testable for free… by clicking below!