Managing Partner at Kreston OPR Advisors LLP
Technical Director for the new Kreston Global Audit Group, a fellow of the Institute of Chartered Accountants of India and has over 20 years of experience in the field of financial services, Transaction Advisory and Risk Assurance practice.
Managing Partner of Kreston-Ezra Yehuda-Rozenblum
Vice President of The Institute of Internal Auditors in Israel, has over 25 years of experience in risk management, internal auditing, and control design and assessment, and specializes in helping organizations understand and assess risks within their operations, assessing the design of processes and controls, and providing tailored solutions to enhance internal audit effectiveness and value.
Audit and technology: the benefits and risks
October 18, 2022
Technology is playing an increasing role in the audit profession, as the ability of IT applications to gather data, analyse patterns, keep records and more becomes ever more sophisticated.
This has come with several benefits for auditors themselves, as well as for the clients they work with. As further technological developments take place, many are predicting improvements in efficiency, cost savings, and the quality of audit work.
But while it’s easy to be swept up by the excitement of progress, it’s also important to recognise the risks and challenges posed by adopting new technology in an audit.
Auditors now need to think carefully about the methods and tools they use, the resources they will need, and the precautions they need to take when using these systems.
Various technologies have a role to play in audit and accounting, but much of the focus in recent years has been on three key areas:
- robotic process automation (RPA)
- artificial intelligence and data analytics (AI&DA).
Each of these technologies offers different benefits to the audit profession across different areas of work.
RPA, for example, works by deploying scripts to carry out routine tasks on top of existing systems. These interact with software applications in much the same way as a human would: copying data from one system to another, for example, or organising that information.
As such, it allows auditors to reduce the time that would otherwise be spent on more basic, repetitive tasks, improving efficiency and productivity, and in many cases allowing for more reliable data collection.
By freeing up time, it also opens up the potential for staff to carry out more valuable, judgement-based work – again, making the audit process more efficient and bringing more value to the client.
And because RPA tends to be highly structured, following a set series of instructions, it’s more manageable and auditable than if these actions were carried out by a human. Through RPA platforms, auditors can see all of the bot’s activities and the exact tasks it has completed.
Blockchain can provide transparency benefits to an even greater degree. Developments like smart contracts and payment systems built on immutable, decentralised ledgers offer the potential for solid audit trails and more reliable financial reporting.
AI&DA technologies, meanwhile, can provide powerful tools for analysing patterns in large volumes of data, potentially removing the need for sampling as part of the audit process.
This can be used to identify and highlight anomalous transactions, which an auditor can then investigate further.
While these technologies have potential to enhance audit processes, there’s still a risk of error, human or otherwise.
For example, while data stored on the blockchain is by nature unchangeable, that doesn’t mean it’s fraud or error-proof – there’s no guarantee the information was entered correctly in the first place.
This can present real risks to the integrity of data recorded this way, with potentially major economic consequences if tools like smart contracts are used on a wide scale.
Similarly, the quality of data produced through automation (either RPA or AI&DA) will greatly depend on the quality of data going in. And once you have your results, these still need to be interpreted and understood by a human.
Anomalous data identified through AI, for example, might turn out to be a false alarm and not an audit concern at all. To avoid time wasted or data being misapplied, this information should be managed by someone with statistical awareness and that they use their judgement in interpreting the results.
For auditors implementing new technologies, it’s important to have oversight of the applications being used, to monitor them consistently, and to have at least a functional understanding of the technology and its limitations.
As more automation is put in place, many people fear their jobs will become obsolete, and that concern is just as present in the accountancy industry as anywhere else.
While it’s true that automation will remove the need for staff to manage certain manual tasks themselves, proponents of these technologies often argue that they’ll simply change the nature of peoples’ jobs.
With the more basic tasks taken care of, there’ll be a greater need for roles that require human analysis and judgement – ones that are ultimately more valuable to the audit firm and its clients, but also, in many cases, more interesting and fulfilling.
That said, it’s important to take employees’ concerns seriously when adopting new technology. Employees might not only worry that their role will become redundant but also that they’ll lose an aspect they enjoy, or need to retrain in a new field.
Automation might require junior staff to carry out more complex, judgement-heavy tasks at an earlier stage of their career than before. In turn, this might present challenges for managers overseeing that work.
Another risk comes with the increased use of AI, such as machine learning. Compared to more routine automation, implementing AI gives the software greater autonomy. That can allow for more sophisticated activities, but it also means less visibility on how the results are produced.
AI might act in unanticipated ways and leaves virtually no audit trail to explain how it reached its conclusion. This lack of visibility means auditors cannot rely on its results or use them as evidence.
Currently, AI and data analytics are not widely taught in accounting studies, leaving a knowledge gap in the industry.
To make the most of the opportunities offered by this technology and avoid misinterpreting or mishandling its data, audit professionals will need to upskill to understand the fundamentals of how it works.
Finally, there are several important ethical questions to consider when looking at new technology in audit.
Blockchain, for instance, is notoriously resource-intensive to run. The amount of energy required to operate systems on the blockchain is significant not only for its financial cost to the business, but also for its environmental consequences.
AI&DA, meanwhile, often requires data to be collected in large volumes, which can lead to its own ethical and legal issues. Audit firms or other organisations implementing machine learning should think carefully about their data source and its compliance with legal frameworks.
For example, those based in the EU or handling data from people in the EU will need to think about how they’re meeting the requirements of the general data protection regulation (GDPR), as well as its UK equivalent.
Talk to us about the impact of new technology on audit.