Following a string of high profile business failures – and the economic implications of COVID-19 – the role and quality of audit is under the spotlight, with many demanding change. From the initial economic freefall to the role of government financial support and the struggle to get back to ‘business as usual’, balance sheets have become extremely fragile.
A drastic and strategic change in the audit process is now more vital than ever. The industry must move from an outdated, rules-based audit approach to a methodology that focuses on proactively identifying and managing risk. Shifting from a static annual audit process that only reports after the event – and therefore misses vital information to a near-continuous, data-driven approach will enable rapid, actionable insight to be used not only within the audit itself, but across the entire business.
Stuart Cobbe, Director of Growth, Europe, MindBridge outlines the role of machine learning, artificial intelligence (AI), and a risk-based approach to rebuilding faith in audit and providing businesses with tangible, lasting, and provable business value.
Embracing the need for change
The Brydon Review into the audit market called for fundamental parts of the audit process to improve. This cannot be ignored. Indeed, the Wirecard scandal only highlighted the need for a more investigative and forensic audit process, calls that were echoed by the IDW, the professional body for auditors in Germany.
Furthermore, traditional rules-based audit is outdated and inadequate to fulfil audit’s purposes, especially in a post-COVID-19 economy. It is widely recognised that audit’s methods have not kept pace with the increasing level of business complexity or the disconnection between management teams and investors. Nor has audit kept pace with the opportunity that technology presents to support business, which is only creating further frustration for auditors.
Having said that, technology has been used within the audit process, but leveraged mainly to automate the checklists and rules that govern the way audit has historically been done, rather than to challenge the different ways of approaching the audit with the use of technology. Simply automating the old ways are unlikely to mitigate the risk of business failure – a risk that COVID-19 has only exacerbated.
The question remains: why do we, as an industry, spend so much of our time working through endless checklists and verifying standard invoices, rather than actively seeking to understand the key areas of business vulnerability? Why spend time manipulating data to identify outliers instead of investigating those outliers and understanding the implications on the business? At what point does compliance stop the talented people in our industry from providing value and in doing so, fulfil their duty to businesses, shareholders, and the wider public?
This daily frustration of working through a checklist can be avoided by leveraging the auditor’s high level of knowledge and skills to interpret the key financial information of a business. By investing in new technologies and embracing a risk-driven, agile way of thinking about the work, auditors can provide the assurance needed and implement the changes many in the industry are so desperately clamouring for.
New challenges for CFOs
COVID-19 has accelerated the trend toward increased digitisation within businesses and illuminated the challenges with auditing complex organisations. As such, COVID-19 has acted as a catalyst for this essential change as CFOs recognise the need to rapidly understand the new business landscape and identify priority areas of risk.
In this new climate, CFOs must, for example, assess how confident their firms are in their use of the government’s financial support. From the accuracy of furlough claims and the challenges of repaying deferred VAT payments and loans, to the risk of these funds being misappropriated by employees in personal financial distress, government funding has created both a lifeline and a new set of challenges to overcome.
Allowing the data to speak for itself
Auditors are perfectly placed to support companies as they go through financial turbulence and provide the vital insight needed around areas of unexpected activity. Timely identification of risk can help firms avoid a catastrophic crisis and deliver real business value, which can all be enabled through sophisticated machine learning and AI technology. Unlike the human eye that can only see what it expects to see, intelligent technologies have no preconceptions and allow the data to speak for itself. The algorithms can work through the data, find patterns and reveal insight – insight that would be almost impossible to discover manually.
Rather than using a checklist-driven approach, a risk-driven, machine learning-enabled investigation gives the foundation needed for a new level of business insight, as well as a new-found confidence in audit. Whether it’s revealing unexpected trends in invoice realisation, identifying mistakes, or flagging potential employee fraud, the audit firms that embrace this data-driven, risk-focused approach can rebuild corporate faith in the value and quality of the audit process.
Importantly, this methodology recognises that although annual audits can do the job, they are often too late to be insightful to key stakeholders and therefore provide business value. Organisations have steadily moved from quarterly to monthly, to daily reporting and often real-time data for their internal reporting; there is no reason for this not to be the case for external audit as well. From reconsidering existing operating models to developing new service lines, there is a real chance to provide increased value to the world economy through enhanced, timely business insight.
This change in strategy provides the opportunity to redefine audit as we know it. It must be remembered, however, that this is not about utilising robotic technology to automate audit processes and reduce employee workload. Instead, it is about giving auditors a way to deliver real value whilst addressing the challenges and complexities of modern business models. Fundamentally, risk-based audit moves away from a one-size-fits-all approach to one that truly reflects the state of each individual client’s business. Audit data becomes meaningful, relevant, and above all, valuable.