How to use data analytics to improve your internal audit function

More and more auditors are using data analytics in audit to improve their internal audit programs and processes as well as deliver a more business-centric audit function that can focus on higher-priority risks. ACCA, the global body for professional accountants, notes that “businesses are finding increasingly sophisticated and timely methods to utilize data analytics to enhance their operations.”

Whether your audit team monitors and assesses risk daily or reports aggregated risks to your board and stakeholders, data analytics can play a crucial role. Harnessing data analytics via an appropriate audit management solution can support you in transforming audit into a more focused, efficient, value-led function.

The role of data analytics in the audit process

As internal audit teams seek to transform their functions from reactive, reporting-led assurance to trusted business advisors and partners, there is a central role for data analytics in audit. This change in focus and perception demands an agile function, proactive rather than reactive.

This reimagining of the internal audit team and how they approach their audits will see the entire audit lifecycle evolve into a value-driven process. One that moves from isolated data-gathering and analysis to organization-wide oversight, employing next-generation analysis and reporting software that can provide assurance on financials and compliance – freeing up auditors to focus on other risks.

“How do we save time without reducing the level of assurance?” said Tom Keaton, Director of Internal Audit at Crown Castle. “You need to start with the financials, which are going to be easier to automate. Then connect data across systems to give new insights.”

9 benefits of data analytics for internal auditors

Data analytics and auditing are natural partners for numerous reasons. For internal auditors, the ability to use data analytics delivers nine tangible and significant benefits.

Data analytics in audit benefits:

Improves data quality. ACCA calls this the “main driver of using data analytics” for auditors. Conversely, as the audit body, ICAEW, notes, in audits, “trust can be rapidly lost due to inaccurate or unreliable results, which can be caused by poor quality data.”

1. Empowers auditors to analyze and audit large amounts of data, including testing the entire population.
2. Helps auditors to prioritize risks based on likelihood and impact.
3. Allows risks to be viewed in the context of broader organizational objectives, operations and priorities.
4. Enables the audit plan to align with capacity, risk potential and risk tolerance.
5. Supports the execution of the audit process through comprehensive documentation and clear recommendations.
6. Delivers usable insights; data analytics in audit doesn’t just benefit the audit team but the wider business, enabling clear communication of risks and mitigation strategies.
7. Provides a clear picture of compliance, enabling audit teams and the entire organization to visualize and drive continuous improvements in approach.
8. Drives greater efficiency throughout the audit lifecycle.

Challenges of harnessing data analytics for auditors

It’s clear, then, that data analytics in audit has significant potential to improve the robustness of audits while smoothing the process and delivering a business-oriented approach to audits.

There can be challenges along the way when looking to harness data analytics.

3 challenges of utilizing data analytics

1. Acquiring comprehensive and accurate data. In organizations where “audit big data” isn’t routinely captured and isolated data-gathering is the norm, moving towards a state where data analytics for auditors can be optimized can be a challenge. Deploying software that leverages AI and robotics to automate data collection, as well as prepare and analyze data, can help mitigate this challenge.
2. Deciding who should be involved in the process. If data analytics and audit aren’t already intertwined in your business, you’ll need to make decisions about resources. Not all solutions integrate across your whole business, with a focus on governance, risk, audit, compliance. However, this can lead companies to have to start from scratch later. Consider not only who should be involved today but who you will work with in the future. You’ll want a solution that can integrate fully, even if you start small today. This will prevent you from having to create a new program or onboard a new tool from scratch later. If you’re an internal audit manager or controller, this is something worth flagging to your boss.
3. Choosing the right technology to employ for data analytics. This is often one of the biggest challenges for internal auditors/controllers, the head of audit and CFO. This article will outline key considerations to help you navigate this. 

How does technology help?

Technology fundamentally underpins auditors’ ability to harness big data and employ data analytics in audit. The ICAEW notes that the growth in the use of data analytics as “an indispensable element of the internal audit toolset” has been enabled by “fast-evolving technologies that generate-increasing amounts of data.”

Making the right decision about the technology your organization uses to support data analytics for audit can be the difference between success and failure. Let’s explore some of the considerations.

5 questions to ask when buying a data analytics for auditors solution

There are some fundamental questions to ask when investing in a solution to deliver data analytics in audit.

1) Analytics designed to detect risk

Too many audit management solutions are built without input from the teams that will use them. Instead, you should opt for software built specifically for audit analytics, with attention to the support audit teams’ needs. Here are two factors to help you gauge whether a solution is audit-specific.

• Preloaded audit tests: Many audit management solutions integrate with third-party data analytics tools that weren’t specifically designed for auditors. This means that they have very broad capabilities. While that sounds great in theory, it can be a disadvantage. Third-party analytics tools require a data scientist or your IT team to write the audit scripts for you. Consequently, you may be left relying on these stakeholders, which can take a very long time and hold you up, even if you have someone within your company with the expertise to write these scripts. A data analytics tool that is designed for auditors will likely already have pre-built audit scripts, which are much easier to implement.
• 100% testing vs. sampling: A solution built with audit at its heart will also deliver the rigor you need, for example, by providing 100% testing rather than sampling data. Often, audits can use substantive analytical procedures to protect against fraud and ensure all controls are in place and functioning as they should accurately. Examples of substantive analytical procedures include examining the processes used to prepare an organization’s financial statements and testing the disclosures. While valuable, these processes can provide incomplete data. A solution employing 100% testing enables auditors to provide complete assurance to their directors and to the board.

2) What are the additional costs?

The cost of a data analytics solution for auditors is a significant factor in your decision process. If your chosen solution doesn’t do everything you need, you may have to invest in multiple purchases to get your desired outcome.

It’s also vital to evaluate the costs of a solution that uses third-party analytics tools (which we look at in more detail below). Additional costs around connectivity and additional tools needed to bolt on third-party analytics tools can be significant, with organizations having to spend up to $100,000 on top of the audit management solution they are already paying for.

3) Does the software provider have a service that can set up your scripts?

When we break down data analytics in audit, typically 80% of the work is around accessing, normalizing and cleaning data, and only 20% comprises analysis. Your approach should reflect this in terms of resources, time and focus.

However, many audit teams don’t have the in-house expertise to access, normalize, and clean their data or advise on how to automate it. When you look for a software provider, it’s essential to choose a company that can set up the scripts you need to do this within the solution.

4) Can the solution grow with your company?

Your organization is evolving strategically. In tandem, your audit department is maturing, with growing responsibilities and a shift from the tick-box to the consultative.

Your chosen data analysis and auditing solution need to adapt to the development of your organization and audit function. Questions around scalability that you should ask include:

• Does it have in-built data connectors that allow you to link up data and systems across the enterprise, such as SAP, Oracle and Concur?
• Are analytics built in to harness the information you need to drive further improvements?
• Does it have time-saving features that deliver economies of scale as your business grows?

As CAE or head of audit, streamlining and efficiency are your watchwords. Avoiding silos and integrating your risk management with your GRC strategy and ESG solutions will support your organization-wide audit capability and risk management strategy. As a result, your audit function can demonstrate more purpose-driven, efficient and strategic leadership.

A solution that can grow with you as your audit program matures can help to future-proof your program and ensure it won’t hit a growth ceiling. And if your chosen solution can solve many use cases, both traditional and non-traditional — for instance, audit, risk and compliance — you create a more risk-aware culture within your entire organization.

5) Does the tool empower you to focus on the important work and fewer mundane tasks?

A tool that uses automation can dramatically improve day-to-day work — and, therefore, job satisfaction — for internal auditors and audit managers. Automating data analytics in audit using dynamic, automated workflows reduces repetitive “grunt” work and streamlines processes. It also minimizes human error, reducing the need for rework.

Doing this, and enabling continuous testing, rather than sampling via substantive analytical procedures, enables internal audit teams to explore what HAS gone wrong, rather than what could go wrong — and, as a result, drive continuous improvement.

The analytics behind the tool powers this analytical, investigative approach. Give due consideration to this, and you will accelerate the audit team’s ability to act as a trusted advisor, delivering continuous assurance and insights from organizational data.

When looking for a tool that enables data analytics in audit, ask whether your chosen solution supports you in focusing your energy on more strategic and critical business risks and analysis.

Discover more essential components when choosing audit management software

The five questions above are the most fundamental to ask when considering a solution to deliver data analytics for auditors. But they are not the only considerations.

You need a solution that provides a single, centralized source of best practice, via templates, libraries and standard procedures. Software that includes audit planning and workflows will enable your team to plan their activity efficiently. Visibility and understanding across the entire organization are maximized by clear reporting and dashboards.

More essential questions and considerations when choosing an audit management solution

Integrated data analytics vs. third-party analytics tools

One question auditors grapple with on data analytics for audit solutions is the “integrated vs third party data tools” debate.

Some audit software uses integrated data analytics, while other companies’ software requires a third-party data analytics tool. There are some considerations for audit professionals exploring their options:

1. Cost

Integrated data analytics tools for auditors are far cheaper than using software that requires third-party data analytics tools and connectors. Some systems require separate licenses and arrangements for data analytics, over and above the initial cost of the audit software; the additional security protocols needed can make this very expensive. The Diligent audit management solution has data analytics inbuilt, so there are no nasty surprises in terms of extra costs for separate tools and integration technology.

2. Customer Support and Troubleshooting

If you opt for a solution that relies on third-party data analytics tools and experience problems, you must resolve the issue via the third party, not your original supplier. With a fully integrated data analytics tool, you’ll receive a more streamlined service, with all your customer support from a single source.

3. Future-Proofing

As mentioned above, a solution that can future-proof data analytics in audit is vital. A solution that relies on third-party data analytics software makes scalability more complex, whereas one with integrated data analytics for auditors means you only have one system to consider as your business evolves.

Streamline your approach while increasing assurance

When exploring the benefits of data analytics for auditors — and deciding what software can support your audit transformation — you need a solution that not only decreases your workload but increases assurance and confidence.

And because you need not only a workflow tool but a way to maximize the potential of data analytics in audit, you must ensure your chosen solution ticks all the boxes.

Having acquired ACL Analytics through Galvanize, Diligent’s analytical capabilities are built on Audit Command Language (ACL) to provide our clients with that high level of assurance while enabling audit teams to do more with less by automating audit processes. You can dig deeper into our audit management solutions and find out how they can accelerate data analytics for auditors.