Moving internal audit toward robotic process automation (RPA)

Part 1: A structured RPA methodology for leveraging automation

To launch our three-part series, we examine one of the most prominent disruptive technologies on the market: robotic process automation. When deployed successfully, RPA can significantly reduce and—in some cases—eliminate the need for human intervention in performing low-value, mandatory audit testing. By allowing internal audit professionals to spend even more time on strategic activities, advanced RPA can promote greater collaboration among the three lines of defense, with the ultimate goal of enabling an integrated approach to risk management.

Common situations for applying RPA

• Gathering background information and metrics from multiple systems or sources to better define audit scope
• Continuously monitoring business operations that would be too demanding and/or expensive if done manually
• Prepopulating documentation requests based on audit scope
• Generating planning documentation by automating text-heavy documents
• Performing “what-if” analysis on more data more frequently
• Detecting suspicious logs associated with IT systems
• Real-time reporting of frauds arising in financial systems
• Testing control effectiveness based on a sample or the entire population
  

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Part 2: What internal audit teams might consider when auditing automation

In our second installment, we explore what can happen when modern automation tools enter an organization and what they bring with them: new risks. We consider where different IA organizations stand with respect to their auditing automation and cognitive technology journeys, based on the results from a recent digital survey.

Ultimately, the success of an enterprise automation program will likely come down to its ability to scale with efficiency and effectiveness. Here, IA can play a valuable advisory role by providing insight into leading practices for reducing risk while also being a guiding light for increasing ROI.

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Part 3: Scaling automation capabilities in internal auditing

To wrap up this series, our third installment offers a blueprint for scaling digital capabilities and transforming the audit life cycle. It’s one thing to deploy a digital tool to enhance a specific process or control and entirely another to implement an automation program aimed at transforming the IA organization. Effectively scaling analytics and automation capabilities requires a thorough understanding of what automation is and isn’t, along with focus, long-term commitment, and a clear vision of what a digitally enabled IA team looks like.

Explore a six-step approach designed to assist IA leaders in overcoming common hurdles to implementing a digitally enabled IA operating model. This will enable internal audit leaders to more confidently begin to move analytics and automation beyond theory and toward actualization of the ultimate goal: creating an agile, insightful, and resilient IA organization that adds value to the business.

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Conclusion

The three parts of the series share a common theme: Ready or not, automation and cognitive technologies are here to stay. As such, these digital resources should be adequately governed and fully integrated into the operating model of the IA function. While the challenges of managing a digital workforce alongside a human one are significant, IA organizations that fail to incorporate these capabilities may be disrupted. Without the help of digital resources and talent, it’s unlikely they will be able to keep up with the changing risk landscape and the evolving needs of the business.

Our Digital Internal Audit services

Technological advances and trends in advanced analytics, robotic process automation, and cognitive intelligence are rapidly reshaping business models, improving productivity, and enabling innovation in the way organizations operate and conduct business. Our Digital Internal Audit team helps departments assess and understand the new opportunities associated with these technologies so they remain proactive in advising senior management on preventing and detecting new and emerging risks.

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