Here’s a question for you: How long would it take you to manually classify 6,000 regulatory rulebooks with one million regulatory paragraphs, against a specific regulatory theme, like AML?
The answer is likely several years; consuming a large team of high-cost regulatory experts, each applying subjective interpretations and not always getting it right.
How long would it take CUBE to do the same job? Just TWO hours, without human intervention.
The pace of regulatory change isn’t slowing. The manual management of the 57,000 or more regulatory changes issued by regulatory agencies annually is proving unsustainable. If you don’t think compliance is a key element of your digital transformation strategy, think again. With repetitive tasks underpinning the vast majority of regulatory change processes, there is ample opportunity to transform compliance from a reactive and risky business into one that is responsive and forward-looking.
CUBE was the first RegTech firm to transform regulatory change management with our inventive, pioneering application of Artificial Intelligence (AI). Almost a decade ago, we embraced and fully optimized transformational technologies, including Natural Language Processing (NLP), Machine Learning (ML) and Robotic Process Automation (RPA), to inject science into compliance.
Our DRP far exceeds the capabilities of ordinary regulatory data providers. The true value of CUBE is not only in the tracking of global regulation and continuous monitoring of regulatory change (although our approach to horizon scanning is admittedly very cool).
What really excites is the way we enrich a mass of regulatory data to make sense of it. We automatically classify regulatory statements, we have built a suite of best practice, and we offer thematic regulatory ontologies that can be mapped against your own business taxonomies. With CUBE, you can slice and dice regulatory data, fully-automate impact assessments, and produce regulatory gap reports in an instant.
For pioneering automation of regulatory change management, consider CUBE.