Delivering audit value with data analytics

The Oxford English Dictionary defines a revolution as “a great change in conditions, ways of working, beliefs, etc. that affects large numbers of people”. This accurately describes the transformation that was already underway in audit before the COVID-19 crisis. With advancements in technology, the use of data analytics, artificial intelligence and machine learning are fundamentally changing how business works. Resistance is not only futile but seems to put companies at a competitive disadvantage. The COVID-19 crisis will only serve to accelerate this process, and professional services firms are no exception.

When we hear buzzwords like 'data analytics', 'artificial intelligence' and 'machine learning', it can be intimidating. Many people don’t fully understand such concepts, but in truth, you don’t need to. You just need to get comfortable with them. And you probably already are: familiar services like Netflix or Spotify use artificial intelligence to understand your preferences and make subsequent suggestions based on that knowledge. The level of consumers’ expectations is continually increasing, and the successful companies are those that are advancing with technology. The same is true for businesses and their expectations. In audit, the revolution is underway and the sections that follow highlight the key drivers for this change.

The volume of data available to auditors is astounding, but in most cases, this data is simply not being used. If this were happening in any other industry, there would be questions to answer. Data analytics can improve the audit experience in several ways, for both the audit team and for the client.

During the planning phase of the audit, audit teams must shift their focus away from the old mindset of “what could go wrong?” Through analytics, we can turn our attention from what could go wrong to what has gone wrong. Auditors have access to the client’s complete financial data for the period under audit – if they focus on analysing and understanding the data, they could identify an unexpected transaction or trend in the process. During the execution phase, auditors should also build on the knowledge gained in planning to truly understand the business in question and focus their attention on higher risk transactions. Finally, auditors should move away from a ‘random sample’ approach and, instead, focus on the transactions that appear unusual based on their knowledge of the client, business or industry. These are just a few areas where improvements in audit quality can be achieved using data analytics.

In the examples above, the use of data analytics in planning will identify what has gone wrong and any associated unusual transactions. In execution, these transactions will be tested as part of the audit sample. It could also cover some requirements under auditing standards concerning journal entry testing, as the journal entries will likely be the data that highlighted what went wrong in the first place. Again, this is just one example of efficiencies gained without even considering the hours saved by automating processes like creation of lead schedules and population of work papers.

The world will be a very different place in years to come. Firms with the ability to perform in-depth analysis using data analytics undoubtedly have a significant advantage over those that do not, given the efficiencies they can gain and the potential reduction of physical evidence required from clients, among other things. Due to the changes we have all had to endure, auditors may also have additional procedures to perform (e.g. roll-back procedures where they were unable to attend stock counts at year-end due to the COVID-19 closures of businesses). Such procedures have the potential to be automated, saving even more time and effort for audit teams.

Rather than spend time performing mundane tasks such as testing large randomised samples, data analytics allows audit teams to jump into the unusual transactions. This will make the job more interesting to auditors and cultivate a curious and questioning mindset, which will, in turn, lead to improved scepticism and audit quality.

This might happen in two ways. First, the time saved by the client’s staff (who, in theory, will have fewer samples for which to provide support) and second, through the value the audit adds to the business. As an example, consider an audit team performing data analysis on the payroll for their client. As payroll is a standardised process, the audit team has an expectation around the number of debits and credits they would see posted to the respective payroll accounts each month. As part of their analysis, however, they find an inconsistent pattern. This can be queried as part of the audit and the client will be better able to understand a payroll problem, which they were previously oblivious to.

Given the level of data analysis that occurs daily in the life of anyone using a smartphone, a consistent, high quality is understandably expected in people’s professional lives, too. Audit clients, like all consumers, want more. They want a better and faster audit. They want an audit that requires minimal interference with the day-to-day running of their business, without compromising the quality of the auditor’s work. With troves of data now available to auditors, such expectations are not entirely unreasonable. Audit firms have access to vast amounts of financial and related data – in some instances, millions of lines of information – that, if analysed robustly and adequately, would improve their processes, their clients’ experience, and the quality of their audit files.

Audit professionals can often struggle with work-life balance. Though most firms are getting on top of remote working, the hours in busy season are long. In a time of continuous connectivity, the time frame around ‘busy season’ is also becoming blurred. Through the use of technology, we will one day make auditing a 'nine to five' job. Many will scoff at that idea and, although I do not expect this to happen in the next five years, or even ten years, it is possible. By automating mundane tasks and continuously upskilling our graduates, we can transform how an audit team completes work. There will be more scope to complete work before clients’ financial year-ends, thus moving much of the audit out of the traditional ‘busy season’. Machines can complete specific tasks overnight so that auditors could arrive at their desk, ready to work on a pre-populated work paper that needs to be analysed by a person with the right knowledge. With appropriate engagement by all parties (i.e. audit teams, senior management, and audit clients), we could significantly reduce the hours spent on audit engagements and give this time back to auditors. Along with attracting high-calibre graduates, we will retain high-quality auditors in the industry while also avoiding mental fatigue and burnout, which will again lead to better quality audits.

Graduates joining firms in recent years have particular expectations of the working world. They want job satisfaction, flexible hours, remote working, and an engaging role that will challenge them. Professional services firms have to compete for the very best graduates, and no longer just against each other – a host of technology-enabled businesses are attracting talent on an unprecedented scale by meeting the needs listed above. Technology, and data analytics, in particular, can offer the solution to the graduate recruitment challenge – by making the work more efficient and automating mundane and repetitive tasks, graduates can instead focus on analysis. When people find their work challenging and interesting, they will feel more engaged.

This move towards technology is not without its risks to the profession. Automating basic tasks removes the opportunity for graduates to form a deep understanding of these sections of the audit file. The onus is therefore on the current cohort of Chartered Accountants to take the reins, both to drive technology advancement forward and also provide practical, on-the-job coaching to ensure that this knowledge is not lost for the generations that follow.