The orchestration of Regulation Transformation Engine (RTE), to deliver our award winning RegPlatform.
CUBE RegTransform is our AI-powered service that is completely unique to CUBE. RegTransform powers CUBE technologies and is the critical component behind CUBE’s interface that enables effective and accurate regulatory data management.
RegTransform is the technological magic that transforms regulatory data into regulatory intelligence at a scale and quality not possible at a human level.
Create lineage
From the moment we identify sources, to the time that they are published for the end-user, we create lineage across regulatory data. Through CUBE RegTransform we bring together a series of sophisticated processes, that work seamlessly to transform all regulatory data into regulatory intelligence.
This means that when regulatory change occurs anywhere in the regulatory internet, no matter how small, we know about it, as do our thousands of end-users who are able to put change processes in motion, fast.
Identify
CUBE RegTransform identifies every source of global regulatory data, regardless of morphology. Drawing on years of industry experience, CUBE machine reads the whole regulatory internet to establish any source pertaining to financial regulation, so you don’t have to.
Monitor
Once identified, CUBE RegTransform continually monitors all regulatory data sources. It leverages machine learning (ML) and natural language processing (NLP) to monitor the content and track any and all changes. This ensures all regulatory data within CUBE is consistently accurate and up to date, in real time. Where change occurs, it identifies what that change is, and where it takes place within the source. All sources are versioned, enabling the end user to compare renditions and see historical changes.
Capture
CUBE RegTransform machine reads the entire regulatory internet, regardless of form, and captures the content of all regulatory sources in their entirety. As well as capturing the content, machine automation captures the structure of the source, including morphological features such as headers, links, footnotes etc. This level of granularity means that any changes within the source are detected as they happen; from changes to entire regulations down to individual words and characters. Our sophisticated artificial intelligence (AI) is trained to eliminate false positives to ensure all returns are accurate and meaningful.
Structure
Once captured, every regulatory source is deconstructed down to the lowest common denominator. It is then recompiled into a common structure through a process of normalisation. This structure is pervasive across every data piece that CUBE consumes and takes the form of a consistent, proprietary schema that is fully tagged to identify every element of the structure.
Translate
Neural engines automatically translate global regulatory data from all native languages to English. Once translated, the source document is continually machine read so any changes made to the native language version are captured and translated. Native language records are stored so that end users can see both native and English versions side by side, as well as compare historical renditions. CUBE’s automated translation techniques have been developed over a number of years and are consistently validated to ensure accuracy.
Classify
When new regulatory content is published, or existing content altered, CUBE RegTransform harnesses machine automation to classify the source and assign it to an appropriate model within our Ontology. Our bespoke ontological models interoperate and map the data within a regulatory index, depending on its assigned classification. This results in millions upon millions of classifications, which are instantly, semantically organised into a logical construct. Classification is fully automated and conducted at a speed and scale that is incomparable to existing manual processes.
Extract
CUBE RegTransform understands the context and narrative of all regulatory text and identifies where there are rules, requirements or meaningful information – explicit, implicit, inferred or otherwise. It then extracts that information from across regulations, whether they’re in the body text, citations, summaries or elsewhere, which is then used to enable machine reading, execution and to support regulatory data processing within CUBE.
Enrich
Where a regulation or rule is published, CUBE RegTransform makes intelligence-based decisions about whether it links to existing regulations or content. Using AI and NLP, it establishes regulatory links, which build out an enriched data register.
Validate
Processes and decision making are validated at every stage within CUBE RegTransform. CUBE’s regulatory subject matter experts (SMEs) work alongside machine feedback to Q&A across the data journey. From identification, through to translation and enriching, each regulatory source must meet a stringent rules-based validation process. This ensures that all CUBE data is relevant, up to date and compliant with our data model.
Publish
Once a regulatory source has passed through each stage within CUBE RegTransform, and met CUBE’s stringent validation criteria, it is published in a consumable format for the end-user.
RegOntology
Mapping regulations to cut out the noise and understand what’s relevant, and what’s not.
RegDashboard
A personalised dashboard that ensures you are only alerted to the changes that matter to you.
Discover
RegPlatform®
Our world-class SaaS platform, providing a holistic solution to complex regulatory change management for global financial services. Our RegPlatform product combines industry leading technology with expertly validated insights to present regulatory intelligence.