The Client's Guide to Data Analytics in Internal Audit

HOST: ANN BLAIR JAMESON: Welcome back to the Risk Advisory podcast. I’m Ann Blair Jameson, a senior manager in the Risk Advisory practice at Cherry Bekaert, and I’m joined by my colleague Yanni Diaz, a Risk Advisory director.

Today, we are excited to discuss data analytics in internal audit. This is the third episode in our series celebrating the IIA’s Internal Audit Awareness Month.

Make sure to check out the first two episodes in this series at cbh.com/podcast. In today’s rapidly evolving business landscape, data analytics has emerged as a powerful tool that can transform how internal audit teams work and conduct testing.

Both public and private companies stand to benefit immensely from incorporating data analytics into their internal audit processes. Today, we’ll focus on key benefits of implementing data analytics and ways that Cherry Bekaert can assist with this implementation.

Yanni, thanks for joining me for part three. To start us off, can you give us a brief overview of data analytics for those who might not know?

GUEST: YANNI DIAZ: Happy to be here. Data analytics is the process of sorting through and examining pieces of data or information to find patterns, trends, or important details to help us understand the bigger picture.

It is the process of turning raw numbers and information into something useful and understandable, which helps people make better decisions.

HOST: ANN BLAIR JAMESON: That’s a helpful explanation, Yanni. We’ve seen that organizations are increasingly recognizing the importance of data analytics in enhancing their operations.

In your opinion, what are some key benefits of using data analytics in internal audit business process testing?

GUEST: YANNI DIAZ: There are several. First, data analytics allows internal auditors to analyze vast amounts of data quickly and accurately.

This leads to more effective risk assessments. By identifying patterns and anomalies, auditors can pinpoint areas of potential risk and inefficiencies within business processes, which helps guide where they focus their attention.

Second, the use of data analytics streamlines the internal audit process, reducing the time and resources required for manual data analysis.

This efficiency gain reduces the risk of human error and allows the business to spend more time focusing on higher-value activities, such as strategic planning and decision-making.

HOST: ANN BLAIR JAMESON: That is great. I could see how that would be helpful with leadership in their business decisions.

Are there any other benefits to using data analytics for internal audit business process testing?

GUEST: YANNI DIAZ: As a final thought, predictive analytics can forecast future trends and identify potential issues before they become problematic.

This proactive approach enables companies to take preemptive measures and mitigate risks, enhancing their overall business performance.

HOST: ANN BLAIR JAMESON: Those are all great points, especially with the shift of internal auditors to advisors.

The ability to use data for predictive analysis and suggestions to improve business operations is going to be extremely beneficial. Now, let’s shift gears.

Are there areas on the ITGC side where data analytics can play a role in internal audit testing as well?

GUEST: YANNI DIAZ: Absolutely. Data analytics can make a difference in improving ITGC internal audit testing.

HOST: ANN BLAIR JAMESON: What do you see as some of the key benefits to using data analytics within an organization’s internal audit ITGC testing?

GUEST: YANNI DIAZ: There are quite a few. Data analytics helps in monitoring and analyzing IT systems for unusual activities and potential security breaches.

By identifying vulnerabilities in real time, companies can respond swiftly to prevent data loss and ensure compliance with regulatory requirements.

Internal auditors can also leverage data analytics to automate control testing, ensuring that IT controls are functioning as intended throughout the year.

Adding automation enhances the accuracy and reliability of control assessments, leading to better compliance and governance overall.

Most analytics software allows for the automatic generation of reports and notifications to key stakeholders. This ensures prompt mitigating actions can be taken, as opposed to discovering vulnerabilities much later.

Lastly, data analytics provides comprehensive insights into IT operations, helping companies improve governance and oversight.

By analyzing data from various IT systems, auditors can identify inefficiencies and recommend improvements. This ensures IT resources are best utilized and allows leadership to focus resources on higher-risk areas.

HOST: ANN BLAIR JAMESON: That was a lot to process. Do you have an example of one of those benefits you could share with us?

GUEST: YANNI DIAZ: Yes. I once helped a client who wanted to automate testing around credit card transactions.

They used Concur and wanted to check that employees were following the policy and not splitting the same expense into smaller pieces to avoid expense limits.

I helped them with a tool that used Audit Command Language to implement an automated script. This script scanned all transactions for specific rules regarding limits, dates, and amounts.

The script would automatically send a report for review by an auditor. This saved them significant time with data collection and allowed them to focus only on relevant potential infractions.

HOST: ANN BLAIR JAMESON: That’s great, Yanni. For organizations that are excited about the benefits of data analytics but don’t know where to start, what are some important considerations or first steps?

GUEST: YANNI DIAZ: If you are thinking about setting up a brand-new analytics program, it is important to consider tailoring solutions to meet the unique needs of your organization.

Looking beyond the internal audit landscape, aim to have a well-defined strategy and take time to select the right tool before spending money.

By understanding the specific requirements and challenges faced by your company and speaking to leadership, you can develop a customized strategy to improve efficiency across the organization.

Selecting a tool that can serve various functions from a pooled data source allows other departments to easily piggyback off the internal audit program. This makes the initiative very scalable.

It is also critical to provide comprehensive training and ongoing support. Plan for training those who need to adopt the tool to avoid common roadblocks to implementation.

Lastly, be sure to work with your IT and change management teams to ensure seamless integration between the selected tool and your existing systems, applications, and infrastructure.

It can be overwhelming to coordinate a new data analytics program, so feel free to reach out if you have questions.

Cherry Bekaert has experienced professionals who assist clients with integrating analytics tools or selecting tools when first launching their programs.

We can help with every step of the process, from picking the tool to implementation and training. This helps our clients gain easier access without disrupting their operations or straining existing resources.

HOST: ANN BLAIR JAMESON: Thank you, Yanni, for sharing those valuable insights on how data analytics can empower companies to more efficiently conduct internal audit testing.

Looking ahead, we are happy to announce the final episode in our series, where we will explore how to audit artificial intelligence.

Stay tuned for this insightful discussion that will help you stay ahead in the field of Risk Advisory and internal audit.

As always, please like, share, and subscribe to the Risk Advisory podcast. Thanks again for listening, and we look forward to having you join us on our next episode.