While data analytics tools are not a new phenomenon, recent advances in technology coupled with client-side investments in data capture have allowed the accountancy profession to digitize and drive the use of enhanced analytical tools in audit, offering better quality, speed and value the process-as well as greater insights.
By Hermann Sidhu, EY Global Assurance Digital Leader
Analyzing and interpreting data has always been at the heart of the audit process, but only in recent years has the sheer volume of data exploded to the level we see now. While data analytics tools are not a new phenomenon, recent advances in technology coupled with client-side investments in data capture have allowed the profession to digitize and drive the use of enhanced analytical tools in the audit process. This has not only impacted the quality, speed and value the audit can provide but reduces the client burden of supporting the audit and provides greater insights to them.
The foundation for integrating audit technology is obtaining and digitizing client’s data. This has traditionally been a burden for many organizations preparing for audits as collating requests can take focus away from day-to-day tasks. As organizations have become more digitized by investing in new technology, it has become possible to leverage these investments through automated data capture techniques. For our large clients that have centralized their data we capture and process that data centrally, significantly reducing the client burden in supporting the audit..
With advanced data analytics, the audit is also able to provide a new level of insight to clients. For example, EY Helix is a suite of tools that analyses large volumes of audit-relevant data. Our industry-leading Hadoop-based platform has the ability to perform audit analytics at speed using very large datasets. We are also now using advanced tools to analyze unstructured data such as client contracts. By using these tools we’re able to analyze entire populations of data to identify trends and anomalies in the business process and direct our audit efforts to the higher risk areas, limiting random sampling.
Data analytics technologies not only give us more accurate insights to provide clients, but also give our auditors more time and information to use their professional scepticism and support clients with proactive risk management and strategy. By focusing on the risks rather than the data collection and preparation itself, auditors can be forward-looking and predictive, focusing on the issues that matter. That means spending more time interrogating the data: asking sophisticated questions, looking at trends, running comparative analyses and so on.
One area of data analytics that is delivering particular value is Process Mining, which helps organizations to unlock value from the vast data lakes stored away in their ERP systems. Using state-of-the-art mining algorithms, Process Mining helps us to see what is happening at an operational and transactional level of a business, to reconstruct business processes in a more accurate and efficient way than has previously been possible. Process Mining has the potential to transform the way we perform internal control over financial reporting (ICFR) audits for example, reducing the need for sampling while providing key insights to clients.
By providing a transparent view of company systems, Process Mining helps auditors to pinpoint anomalies, identify areas where efficiency savings could be made and put key performance indicators in place to drive continuous improvement. For example, using this technology, EY recently identified a number of ways that a large international client could improve its cash conversion cycle, resulting in significant savings for the organization as a result of the changes.
Having this level of visibility into systems and processes also simplifies a number of business challenges, such as integrating multiple systems following a merger or acquisition, planning an operational restructure or designing a blueprint for automation and collaboration.
The management of risk and regulatory compliance has also been revolutionized by data analytics, helping auditors to identify issues earlier in the audit process, so they can be investigated and helped to be mitigated as soon as possible. For fraud investigations, data analytics and artificial intelligence tools are able to look at structured and unstructured data to identify areas that need investigation. In trading situations, that could mean looking for unusual trading patterns and behaviours, for example.
We have even developed tailored global platforms to help clients monitor and manage the transactions that have taken place, on a continuous basis, and help to make sure transactions are as intended; it’s not always easy for clients to identify if they even have an issue. This is now moving toward real-time monitoring of batch trading data over one day, rather than looking at the previous day’s trading activity.
In a fast-moving world, businesses are under pressure to constantly innovate and deliver results, while fending off disruption and competition from all corners. Survival in this uncertain environment requires a detailed understanding of every area of your organization; what is working, what isn’t working, and where the opportunities and risks are. Integrating advanced data analytics into the audit gives organizations the visibility and vision to stay ahead of the game.
The views reflected in this article are the views of the author and do not necessarily reflect the views of the global EY organization or its member firms.
