Next Gen of Internal Audit

Next Gen of Internal Audit

Artikel erschienen in IT Magazine 2021/06

Transformational components

The objectives of next-generation internal audit functions may be straightforward, but the means by which they achieve these objectives include a range of innovative approaches, tools and governance enablers, including a culture of innovation, that must be tailored to specific organizations and their needs.

In our view, there are three essential objectives of next-generation internal audit groups:

- Improve assurance by increasing the focus on key risks

- Make internal audit more efficient

- Provide deeper and more valuable insights from internal audit’s activities and processes

The specific governance structures, methodologies and enabling technologies that next-generation internal audit groups introduce vary.

Use of Enabling technologies in the Audit Process (image 2)

(Quelle: Protiviti)
For more than a decade, most internal audit functions have posted sluggish improvements in their use of advanced auditing technology. However, extensive reliance on automation, data analysis and a variety of advanced technology applications is a defining feature of next-generation internal audit functions. Common technology activities and tools implemented in next-generation transformations include:

- Advanced data analytics – Leveraging data within the organization to assess risk enables the internal audit group to execute work more effectively (full samples, data-driven flowcharting, risk thresholds, etc.).

- Robotic processes automation – Reducing highly manual tasks within the internal audit function (e.g., generating audit announcements and document request lists, compiling finding summaries) allows the team to focus on risk within the business and areas that require significant levels of judgment.

- Process mining – Challenge traditional approaches to internal auditing by leveraging data to understand processes at a deeper level and earlier in the audit cycle, using data to tell the story of how processes are being transacted rather than through traditional, unreliable, and manual intensive walkthroughs. For example, process mining technology leverages organizational data to automate the process discovery activity and create visual representations of business processes throughout the organization that internal auditors can analyse quickly to identify risk, control breakdowns and inefficiencies. This not only delivers significant efficiency gains but also drives a more effective audit process. Remember, new technologies should not just be «dropped into» the old ways of doing things.

- Machine learning (ML) and Artificial intelligence (AI) – Leveraging artificial intelligence and machine learning enables internal audit groups to increase the effectiveness and efficiency of complex testing, as well as help move complex analysis to more real-time.

The above are just a sample of methods that internal audit should evaluate and incorporate into the delivery of internal audit services. The ease of deployment varies from straightforward (e.g., using optical character recognition or K-means clustering algorithm) to highly involved (e.g., deploying NLP with learning components), but there is a multitude of opportunities for advanced analytics in internal audit, including those that allow for the replication of aspects of auditor judgment. Internal audit should develop an awareness of available techniques and methods to determine those with potential to drive greater efficiency and effectiveness into the internal audit process.

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