Keeping up with regulatory content can be a challenge. The constant changes in today’s regulatory environments translate to a growing burden on organizations in terms of the number of regulations they face and their scope. Many organizations do not possess the necessary regulatory change management infrastructure and processes to address these changes and, consequently, find themselves at a competitive disadvantage and subject to regulatory scrutiny and losses that were preventable. These organizations can greatly benefit from moving away from manual and ad hoc process changes and toward a system specifically designed to manage those changes comprehensively and consistently. Such a system gathers and sorts relevant information, routes critical information to subject matter experts, models and measures potential impact on the organization, and establishes personal accountability for action or inaction. This is enabled with GRC 5.0 – Cognitive GRC technologies that leverage artificial intelligence to provide greater levels of automation.

Many organizations either hire a lot of compliance/legal experts to comb through mountains of regulatory data, or they subscribe to regulatory content subscriptions that do this. This is changing with the role of artificial intelligence applied to a GRC context (Cognitive GRC). Natural language processing, predictive analytics, and robotic process automation make regulatory change management more efficient, effective, and agile for the organization. he U.K.’s FCA Rulebook stacks to six feet tall; this would take a human a year or more to read. A machine can read it, sort it, categorize it, and link it in under a minute. Not only is a machine faster at reading regulations, but it is also more accurate. One Chief Ethics and Compliance Officer (CECO) told GRC 20/20 that they found natural language processing 30% more accurate in reading, sorting, categorizing, and linking/mapping regulations/requirements than humans. A machine stays focused; there is no mind to wander and get distracted.

Cognitive GRC technologies enable a GRC architecture for regulatory change management. Leading solutions in this area are being used to gather regulatory information, weed out irrelevant information, and route critical information to SMEs responsible for making a decision on a particular topic. This, at a minimum, requires workflow and task management capabilities, but in mature systems it provides artificial intelligence to enable this. The old way of hiring an army of subject matter experts as aggregators to manage regulatory profiles, and provide data about relevant new developments is being replaced or at least supplemented by cognitive technologies. Advanced solutions map regulatory changes to the appropriate metadata as part of a fully integrated, dynamic, and agile process supported by artificial intelligence technologies that read and analyze changes and their impact on the organizations processes, policies, and controls.

Specific capabilities to be evaluated in solutions for regulatory change management include:

  • Regulatory intelligence content. Cognitive solutions provide integration and automation with artificial intelligence platforms built for regulatory change to conduct horizon scanning to search for related laws, statutes, regulations, case rulings, analysis, news, and information that intersect with the change and could indicate regulatory risks that need to be monitored actively. The solution needs to automatically capture and access regulatory related information and events from various external sources that are flagged as relevant to the business. This capability helps ensure that regulatory affairs and compliance teams are up-to-date on new, changing, or evolving regulatory requirements. Regulatory intelligence feeds should be easily configured and categorized in the regulatory taxonomy, providing a powerful and comprehensive inventory of changes in laws and regulations. The regulatory content should identify information such as geographic area/jurisdiction, issuing regulatory body, subject, effective date, modification date, end date, title, text, and guidance for compliance. The guidance should give commentary on how regulatory alerts are effectively transformed from rules into actionable tasks and modifications to internal policies and processes.
  • Process management. A primary directive of a defined regulatory change management process is to provide accountability. Accountability needs to be tracked as regulatory change information is routed to the right SME to take review and define actions. The SME should be notified that there is something to evaluate and given a deadline based on an initial criticality ranking. The SME must be able to reroute the task if it was improperly assigned or forward it to others for input. Individuals and/or groups of SMEs must have visibility into their assignments and time frames. The built-in automatic notification and alert functionality with configurable workflows facilitates regulatory change management in the context of the organization’s operations
  • Content management. The solution should be able to catalog and version regulations, policies, risks, controls, and other related information. It should maintain a full history of how the organization addressed the area in the past, with the ability to draft new policies, assessments, and other compliance responses for approval before implementation. The solution needs to provide a central repository for storing and organizing all types of regulations and laws based on various templates and classification criteria within a defined taxonomy. The system should be able to maintain a history of actions taken and analysis, including review periods and obsolescence rules that can be set for regulations.
  • Business impact analysis. The system needs to provide functionality to identify the impact of changes of regulations on the business environment and its operations, and then communicate to relevant areas of the organization how the change impacts them. This is conducted through a detailed business impact analysis in the platform and is facilitated by being able to tag regulatory areas/domains to respective businesses and products. The overall system needs to be able to keep track of changes by assessing their impact and triggering preventive and corrective actions. Furthermore, the solution should ensure that stakeholders and owners are informed, tasks related to actions are assigned, and due dates for the completion of actions/tasks are defined. Similarly, when regulations are removed, repealed, or deactivated, the solution assesses the impact of the change and sets up the appropriate responsive actions.
  • Mapping regulations to risks, policies, controls and more. A critical component to evaluate is the solution’s ability to link regulations to internal policies, risks, controls, training, reports, assessments, and processes. The ability to map to business lines, products, and geographies allows companies to manage a risk-based approach to regulatory compliance. The workflow, defined above, automatically alerts relevant stakeholders for necessary action and process changes. It also supports electronic sign-offs at departmental and functional levels that roll up for executive certifications. Mapping is another area where artificial intelligence/cognitive technologies are providing greater efficiency and effectiveness value for regulatory change management.
  • Ease of use. Regulatory experts are not typically technical experts. The platform managing risk and regulatory change has to be easy to use and should support and enforce the business process. Tasks and information presented to the user should be relevant to their specific role and assignments.
  • Audit trail and accountability. It is absolutely necessary that the regulatory change management solution have a full audit trail to see who was assigned a task, what they did, what was noted, and notes were updated, and be able to track what was changed. This enables the organization to provide full accountability and insight into whom, how, and when regulations were reviewed, measure the impact on the organization, and record what actions were recommended or taken.
  • Reporting capabilities. The solution is to provide full reporting and dashboard capabilities to see what changes have been monitored, who is assigned what tasks, which items are overdue, what the most significant risk changes impacting the organization are, and more. Additionally, by linking regulatory requirements to the various other aspects of the platform – including risks, policies, controls, and more – the reporting should provide an aggregate view of a regulatory requirement across multiple organizational units and business processes.
  • Flexibility and configuration. No two organizations are identical in their processes, risk taxonomy, applicable regulations, structure, and responsibilities. The information collected may vary from organization to organization as well as the process, workflow, and tasks. The system must be fully configurable and flexible to model the specific organization’s risk and regulatory intelligence process.

Ask GRC 20/20, in our coverage of the market as an analyst, what solutions are available for regulatory change management and what differentiates them for your specific needs:

1 comment

  1. Thanks Michael for an insightful article. With the increase in the use of AI/ML and cognitive intelligence, it is feasible to achieve automation in the regulatory world. One hurdle I saw organizations facing, convincing management to invest in this area and adopting to this change. Add to that, there is no one tool or product which can automate this end to end. What are your views on this?

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