CUBE

The unprecedented scale and pace of regulatory change has compelled financial institutions to re-think how they deal with new regulations across multiple jurisdictions and timetables. Throwing light on the current situation, Ben Richmond, Founder and CEO of CUBE states that most financial institutions fail to understand the full extent of their regulatory requirements and consequently don’t have the essential policies and controls in place that ensure adherence to their global regulatory framework. Given the complexity of this challenge, financial institutions require automation that can assist them in understanding as well as implementing regulatory obligations.

As the leader in global regulatory intelligence and change solutions, CUBE enables financial institutions to gain real time insights on global regulatory change, understand the impact of changes to policies and controls, remediate gaps and automate critical compliance processes to implement those changes right through to the line of business, “we take a holistic view of regulatory change dealing with every possible regulatory issue impacting a global financial institution—scale is paramount!”

With a focus on machine automation within the regulatory compliance landscape, CUBE offers an AI platform based on big data, “AI is a significant enabler of how the world of regulatory compliance can be transformed for all financial institutions. The perfect use case for AI is enabling automation in regulatory compliance given the vast amounts of data we have to learn from,” says Richmond. The platform’s machine automated approach collects regulatory data from the open web, analyzes and categorizes the data and extracts the relevant regulatory information based on how it would translate to customers, “we constantly track all global regulations and deliver real-time visibility of regulatory change, across multiple languages and jurisdictions.”

We take a holistic view of regulatory change dealing with every possible regulatory issue impacting a global financial institution—scale is paramount!

Using natural language processing (NLP), deep learning and machine learning to understand regulatory data CUBE then applies those same capabilities to profile its customers based upon key regulatory parameters such as their lines of business and activities, jurisdictions they operate in and products they sell which in turn enables CUBE to understand what global regulatory change impacts the customer and how.

Crucially, CUBE provides an API for its customers to connect compliant controls to systems and data providing the ability for straight-through-processing of regulatory change, “think about it this way, CUBE provides a level of automation that means we can go from a change in rules on selling for example to updating a customer CRM with new controls in near real time ensuring the c u s tome r can adapt to the pace of change— this simply wouldn’t be possible based on today’s typical manual processes.” Through this robotic process automation (RPA) and leveraging its regulatory rule set, firms using CUBE receive analytics on the impact of regulatory change, and automated corrective action to implement those changes. CUBE’s process automation offers a seamless connection of the right regulatory requirements to the right policies and controls, while delivering a fully automated and auditable workflow, integrated with customers’ existing compliance processes, “catering to the needs of an extensive audience of global financial services firms including banks, insurers, asset managers and wealth managers, our SaaS-based platform is being used across 180 countries and in 60 languages,” says Richmond.

“Today, financial institutions spend about 20 percent of their operational costs on compliance and yet we see billions in fines annually, by leveraging innovative technologies like AI and big data analytics, our mission is to dramatically change these statistics and become the standard unified and open platform for all financial institutions to manage global regulatory change,” concludes Richmond.