What if the regulatory handbook was machine-readable and your firm could assess select rules, apply to the business’s data, tasks and actions and interpret this and report back to the regulator at a click of button?
Sounds far fetched right? Well no. The FCA have been focused over the past year on their ‘TechSprint’ initiatives and ran one based on their unlocking regulatory reporting initiative for (the cumbersomely worded) ‘Model Driven Machine Executable Reporting’ (MDMER) strategy.
The FCA wanted to prove that if parts of their handbook were coded so they became machine readable this could streamline regulatory reporting and not only save ambiguity, time and costs associated with this compliance activity but also allow more uniform and accurate reporting and allow both the regulatory and industry participants to identify and manage associated risks.
Some of the participants at the TechSprint published a white paper on the initiative, which focused on how MDMER could aid the industry in interpreting select rules and how the regulator could benefit from validating this approach.
As the FCA stipulate: ‘The benefits of a more efficient regulatory reporting system are clear for both regulators and firms. Beyond a reduction in costs, removing ambiguity – but not judgement – on the firm side would in turn allow for more accurate and uniform industry reporting and faster risk identification by regulators, creating the potential for real time sampling of the industry. Machine readable and executable regulatory reporting would mean changes to regulatory requirements could also be implemented more quickly’.
In April we responded to The FCA call for input and in July we sat on a MDMER tech roundtable hosted by industry consultants Wolters Kluwer and participants discussed key issues, challenges around this initiative. What became clear was although a standardised approach was viewed as the best way forward, with such a disperse industry and diverse set of needs, any digitised regulatory reporting (DRR) procedure would demand a ‘spring clean’ amongst market participants across their legacy technology and data platforms, plus a collaborative 'data lake' could help alleviate the costs for the DRR build and application. From a regulatory point of view, it would make sense for select rules only to become machine readable and offcourse guidance would (in our opinion) remain a human intervention due to its subjective nature.
The role of Artificial Intelligence (AI) plays an important part here where (like other industry’s) it can replace menial, repetitive tasks such as data cleansing and validation and/or support data pattern spotting activities and writing regulations.
This all leads to an AI driven 'Cyber-Compliance' approach where compliance departments could benefit from applying RegTech and DRR in reducing the time required to interpret and apply all the rules manually and report back to The FCA, in other words allowing compliance officers to work smarter.
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