Monitoring and Managing Regulatory Compliance in RPA

Monitoring and Managing Regulatory Compliance in Bots is Critical for RPA at Scale

All industries have important regulations that they must comply with and as organizations expand their automation efforts, many are realizing that compliance is a strong candidate. From an enterprise perspective, the realm of compliance involves adherence to laws, policies, and regulations that are designed to maintain data integrity, data security, and safeguard the privacy of both employees and customers. The processes to maintain these compliance standards are typically stable, rule-based, require structured inputs, manual, and repetitive in nature - the ideal scenario for any organization that is trying to achieve RPA at scale. Those who have implemented RPA are already reporting promising results, such as: 

• Improvement in productivity between 40-50% for regulatory processes that are affected by RPA
• Work availability changes dramatically as bots can be deployed quickly based on demand and work at all times 
• Costs for a bot are typically 20-35% lower than that of a human 
• Error is significantly reduced as bots follow exact scripts without deviation 

However, when organizations are in pursuit of RPA, they often focus more on the value of the technology rather than on what they’re going to automate and the risks that may be introduced in the process. Innovation is not without risk, but when you operate within a regulated industry it’s important to take a step back and determine how to effectively monitor and manage your bots. 

Before implementing RPA, consider the following four factors: 

1. Involve IT from the get-go - In most cases, RPA is initiated by the business side because it’s a lightweight solution that doesn’t require a heavy technical background. However, to truly reap the benefits of RPA it must be scaled across the organization, and in cases like that, IT must be involved from the get-go. When in the pursuit of RPA adoption, organizations need to give sufficient consideration to the importance of strong IT general controls. It is critical to design appropriate security, change management, and IT operational controls to help mitigate the risks associated with unauthorized access to the bots, excessive access to the bots themselves, data loss, or data integrity issues. 
2. Involve internal audit - Engage internal audit or other internal control teams from the starting line to help identify surface risks and ensure that proper governance and controls are established during the process design and discovery phase, prior to bot implementation. 
3. Document, document, document - All your bots should be well documented during their design and development phases. This means a bot’s requirements, system access, designs, and actions should be thoroughly documented, versioned, and stored in a centralized space that can be accessed by team members whenever necessary. This is incredibly important because auditors will want to know if the bots actions match the actions of a person, including exceptions. Read More: What is a Digital Blueprint and Why Do You Need One?
4. Verify outputs - Processing integrity is critical. Just because it does something properly once, does not mean you can set it and forget it. Compliance owners need to make sure the automated processes are completed effectively by monitoring logs and flagging unexpected processing activities or errors. 

Achieving RPA at scale by opening your Center of Excellence

One of the final steps to achieving RPA at scale are establishing your RPA Center of Excellence (CoE). An RPA CoE is a team that’s responsible for driving your RPA initiatives across your organization by consolidating and sharing RPA knowledge, governing RPA, identifying processes to automate, and working with all teams to identify RPA opportunities, deploying bots, maintaining them, and assessing and reporting on RPA.

Learn More: How to Break Down Automation Silos by Creating an Automation Command Center

At this point, it may be a good practice to identify the roles that will make up your RPA CoE, if not the actual team members that will fill those roles. At its most basic, an RPA Center of Excellence comprises of the following:

• RPA Leader – Similar to a product owner, an RPA leader drives RPA strategy, execution, and overall RPA management while also being the initiative’s evangelist.
• RPA Analyst – The main responsibility of the RPA analyst is to identify and assess RPA opportunities (that is, business processes that can be automated), optimize those processes for automation, and monitor the RPA initiative via reporting, providing updates to the RPA leader to present to executive sponsors and the organization where ROI is concerned.
• RPA Developers – Developers are needed to actually develop, test, and then deploy the bots, in addition to providing maintenance and support for any defects, enhancements, or changes in regulations or policies that need to be reflected in the automated process.

The more sophisticated your RPA initiative becomes, the more roles you’ll want to add and employees to fill those roles.