There has never been a more exciting time to explore the transformative potential of technology for audit. The profession has always been influenced by developments and trends in technology but, in recent years, the use of automated tools and techniques in audit and assurance has sped up significantly.

As technologies such as artificial intelligence (AI), machine learning, blockchain and data analytics become more mature, they make their way into ever more products and services, and their adoption increases among auditors and their clients. “The Big Four have always been quick to explore and exploit emerging technologies. Increasingly we see a trickle down into smaller firms and clients, as commercially available tools become more accessible and affordable and elevate the expectations of firms and clients,” says Richard Anning, former Head of ICAEW’s Tech Faculty.

Nigel Sleigh-Johnson, Director of ICAEW’s Technical Strategy Accountability Group and Head of the Audit and Assurance Faculty, adds: “By exploiting technology, the profession has been able to enhance audit quality, increase efficiency at firm-wide and engagement levels, and add value for clients.”

Amid the COVID-19 pandemic, there has been a rapid and widespread uptake of some tech tools. This has highlighted ways in which technology has enabled firms to transform processes and digital interactions between their people, teams and clients.

The shift to video conferencing didn’t just enable home working, it pushed some auditors to make better use of tools their firms had invested in. “Within a week of lockdown, people who previously had no clue how to use our conferencing system were hosting calls,” says Andrew Moyser, Audit Compliance Partner at MHA MacIntyre Hudson.

Audit teams stopped physically attending stocktakes and used live streaming, adapting processes to overcome challenges, for example by supplementing the evidence from their virtual stocktake with other forms of evidence and procedures. “Clients were pleased we could come up with alternatives,” Moyser says.

Not all of the latest tech tools and trends are within the reach of all auditors, or able to demonstrate their usefulness so clearly. The pay-as-you-go on-demand nature of many cloud-based software and services makes it easier for even the smallest firm to dip a toe in the water. However, deciding which of the many available tech tools and techniques can benefit audit firms the most and enhance client offerings remains difficult.

No two firms are alike and the timing of adoption needs to be finely judged. Considerations can be complex and include:

• an organisation’s strategy for assessing and adopting technology;
• software already in use;
• what the organisation wants to achieve with the new technology and within what timescale;
• appetites for change among partners and clients;
• whether and in what way it will address any need to update or develop new skills within the firm; and
• which tools and suppliers seem like the best fit.

The Big Four are using technology to do some impressive things in audit, but it is important to factor in how well resourced they are and the competitive attitude that has been prompted by mandatory rotation and tendering.

For example, in inventory observation, some firms are using drones to capture data as audit evidence. It can enable audit teams to focus more on identifying areas of risk and less on manual stock counts, but it is far from being standard practice even among its advocates.

There are examples of big firm audit innovations that are becoming more widely used across much smaller and less well-resourced firms, such as in data analytics.

Top tier firms have been using data analytics tools and techniques that enable their auditors to dig into relevant data from client systems for accounting, customer relationship management, enterprise resources planning, payroll and so on. Those tools use machine learning algorithms for data analysis and are gradually getting better at identifying anomalies, high-risk transactions and process inefficiencies.

AI and machine learning techniques are increasingly part of big firms’ proprietary tools and commercial offerings from software developers. These systems are getting smarter. For example, they are learning how to read the natural language in documents, such as contracts, then analysing this data and extracting the information that can do most to inform the professional judgements of auditors. Predictive data analytics tools are being used to create models and scenarios that can be used by auditors to question management’s judgements and projections.

Take-away tips

• Monitor Big Four innovations
• Look out for commercial solutions
• Use automation to free up time for adding value
• Focus on what’s accessible, affordable and practical.

Using data analytics to transform complete data sets can be extremely powerful. Armed with 100% of the transactions in a population you can, for example, match 100% of sales invoices to delivery notes, purchase orders and so on, then agree that with all of the cash receipts. Anomalies and exceptions become easier to identify and this frees auditors to spend more time focusing on them.

Some medium and smaller firms may find it easiest to explore data analytics techniques and technologies using tools that many auditors already have access to, such as spreadsheets. In recent years, Microsoft has significantly enhanced Excel’s data analytics capabilities. Excel now includes Power BI, Power Pivot, Power Query, Power View and more. This means that almost every auditor potentially has access to software they can use to slice and dice, filter, sort, query and visualise data for risk analysis, transaction and controls testing, and analytical procedures to gain insights and support judgements.

This may help to explain why the spreadsheet remains a data analytics staple in audit, despite growing availability of specialist tools. “Many of the larger firms now use analytics. We often see it used in journals testing and other areas such as revenue testing. Products vary in complexity, ranging from sophisticated bespoke computer programmes to more straightforward approaches using Excel or similar,” says Lesley Clarke, Senior Manager of Professional Standards at ICAEW.

Self-service analytics platforms such as Microsoft Power BI, Tableau and Qlik are versatile and powerful. “It is possible to use them as the basis of creating a tailor-made data analytics tool for your firm, but this can be costly, so firms should evaluate their free offerings to see whether they may be a good fit for them,” says Mike Whitten, founder of Lambent Consulting.

Take-away tips

• Explore the potential and benefits of familiar tools
• Don’t equate cost with functionality
• Experiment with free/trial/low-cost cloud offerings
• Be proactive and adaptable.

Specialists such as Inflo, CaseWare, MindBridge and Validis offer analytics systems with built-in features and functionality designed specifically for auditors and audit testing. Some medium and smaller firms are already piloting or using these, and practitioners share some of their experiences in the case studies that follow in this guide.

Product offerings are changing all the time, so functional comparisons between different providers can prove challenging. Some auditors have told us that how well a provider understands the particulars of audit and audit firms can be a deciding factor. Also, getting the most from the audit data analytics tools in some commercially available products can demand greater tech and coding skills than others.

In theory, data analytics tools can enable auditors to improve risk assessment processes, substantive procedures, tests of controls and more. Our case studies highlight some of the implementation considerations, but also show that you do not need the resources of a Big Four firm to venture, with some success, into the realms of AI and audit data analytics.

Case study 1 (2020): MHA MacIntyre Hudson

Exploring and exploiting the latest technologies and their potential can help to transform the practice of auditing and deliver value for firms and their clients, as Andrew Moyser, Audit Compliance Partner at MHA MacIntyre Hudson outlines.

“I’d always been interested in computer-assisted audit techniques,” says Moyser, who describes them as being like spreadsheets on steroids. “I was intrigued by the possibilities of audit data analytics.” 

As lead on the firm’s audit innovation project, Moyser has been responsible for bringing data analytics and AI to its audit procedures, a journey that began a few years back by considering the specialised tools the market had to offer.

There were demos, comparisons and assessments for CaseWare, MindBridge and Inflo. “I was looking for how the products scored against a list of criteria,” he says. In particular, how each system could help the firm to add value and enhance audit quality.

The speed of technology advances can make direct product comparisons tricky. “At one point, Inflo had more advanced features and tests, then the next week, something would change on MindBridge and that would have new features,” recalls Moyser. “The products and landscape are constantly changing.”

Despite this, after careful consideration, Inflo was chosen. “I got the feeling that Inflo was easier to use overall. It was definitely much easier to ingest data into, than the other systems.” 

Trials with clients went well. “Audit committees and other non-execs really appreciate visualisations and graphics, showing them what’s going on with seasonality and turnover,” Moyser adds. 

During the COVID-19 pandemic and lockdown, features that supported remote working proved to be particularly valuable.

Case study 2 (2017): Moore Kingston Smith

If the prospect of exploring the professional potential of artificial intelligence makes your heart sink, you are probably not alone. But behind headlines about existential threats to accountants and auditors, the reality is much less gloomy. “There is a lot of hype and building of expectations,” says Karen Wardell, Partner at Moore Kingston Smith.

She knows what she is talking about. Moore Kingston Smith was quick to explore the potential of AI and has had a positive experience. “We wanted to look at what was actually happening and be at the forefront not at the rear.”

Moore Kingston Smith started its journey at an ICAEW presentation on audit data analytics. “We already had high-quality audits and reviews, so we looked at the market from an audit efficiency point of view,” says Wardell. Some off-the-shelf audit automation and data analytics systems call for significant process change and the firm was more open to something it considered to be less disruptive.

It settled on the Ai Auditor platform, developed by the Canadian fintech company MindBridge Analytics. “It was a bolt-on tool for sampling journals, so we thought that it would be a quite interesting starting point.” All general ledger transactions go through MindBridge; it does completeness tests on the data, ranks all transactions on the basis of risk, then selects a sample.

This approach may be more robust than a member of the audit team (who may be a trainee) selecting a random sample based on what they consider to be risky transactions. As Ai Auditor learns from experience, such as the weighting applied to each risk factor by its users, over time it improves its ability to identify normal and risky transactions.

This does not remove the need for auditors to apply professional expertise. “You need to be sceptical about the output; you need to take it and test it, not accept it at face value,” says Wardell.

Focus on the basics of how emerging technologies can help to achieve efficiencies, enhance the quality of services and add value for clients. Moore Kingston Smith has found AI to be accessible and affordable. “Do not be afraid to take the first steps into AI,” says Wardell. “It’s not difficult to implement and it doesn’t have to cost a fortune.”

Take-away tips

• Don't believe the hype
• Learn from other auditors' experiences
• Evaluate product functionality
• Don't forget to consider implementation challenges.

The Financial Reporting Council (FRC) periodically reports its findings on automated tools and techniques in audit, noting practices, potential and progress. In a March 2020 report − The use of technology in the audit of financial statements − the FRC highlights the “step change” it has seen over the three years since its previous report, albeit among the largest audit firms.

This big firm focus need not prevent smaller audit firms from learning from the FRC findings or benefiting from automated tools and techniques.

The FRC notes, for example, that audit data analytics (ADA) has become routine at the largest UK audit firms and that this has been backed by considerable investment in implementing the infrastructure, methodology and training required for effective use. It also notes that third-party vendors of software and other products and services present an opportunity for expanding audit quality and ADA capabilities in audit firms without bearing the cost of investment or building internal teams.

The FRC report highlights the potential for tech tools and techniques to enhance audit quality, including:

• automation of routine audit processes and procedures, allowing extra time for auditors to focus on areas of significant judgement;
• analysis of entire data populations, demonstrating lack of bias;
• using ADA to identify anomalies, deterring fraud and manipulation of accounts; and
• using predictive analytics to challenge and corroborate scenarios, facilitating better challenge of management.

It concludes that “technology has much to offer the auditor in terms of efficiency and effectiveness. It may be used increasingly to support the assessment of the reasonableness of estimates made by management. The potential for the use of technological resources to enhance audit quality is clear. However, it is no replacement for the skills and informed judgement of an experienced auditor.”

For further information, read the FRC report and ICAEW’s response.

Digital technologies are reshaping the world and the rapid pace of development challenges all of those in and around audit. But the profession will evolve, just as it always has. David Lyford-Smith, a Technical Manager in ICAEW’s Tech Faculty, says: “Keep a watching brief and try not to get too bogged down in the nuts and bolts of any one particular technology or system.” Think strategically, but try to stay agile and adaptable.

ICAEW is increasing content in the ACA syllabus on the key technology trends and topics. This includes AI, big data and data analytics, cloud computing, cyber security, the Internet of Things, distributed ledger technologies (including blockchain), and the digitalisation of tax.

ICAEW also provides specialist communities, guides, webinars, online training and other resources to assist, inform and encourage debate.

• Tech's impact on the delivery of audit
• Webinar: How technology is transforming audit
• Risks and assurance of emerging technology
• The essential guide to data analytics
• Tech Faculty resources
• Audit and Assurance