Finance

Rebuilding Faith in Audit with AI

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The role and quality of audit have been under the spotlight in recent years following a string of high profile business failures – and the economic implications of COVID-19 have reinforced the need for change. From the initial economic freefall to the role of government financial support and the slow climb back towards business as usual – albeit in many cases based on fundamentally different models – balance sheets are fragile. 

Audit plays a vital role in safeguarding not only investors’ money but also an organisation’s wider stakeholders, including employees. Yet with traditional methodologies and outdated technologies, few auditors have the opportunity to identify balance sheet frailties in a time frame that will enable critical remedial action to be taken.  

A strategic change in the audit process is essential; a move from outdated, rules-based audit to a methodology focused on proactively identifying and managing risk. Shifting from an annual audit process that can only report after the fact to a near continuous, data driven approach will enable rapid, actionable insight. Stuart Cobbe, Director of Growth, Europe, MindBridge outlines the role of artificial intelligence, machine learning and risk-based audit in rebuilding faith in audit and providing businesses with tangible business value.

Overdue Change

The audit industry must stay focused on the suggestions such as those from the Brydon Review into the audit market, that fundamental parts of the audit process must improve. Following the Wirecard scandal, calls for a more investigative and forensic audit are being echoed by the IDW, the professional body for auditors in Germany. 

Losing sight of these fundamental changes is a problem because the traditional rules-based audit is outdated and inadequate to fulfill audit’s purposes, especially in a post-COVID-19 economy. Audit’s methods have not kept pace with the growing level of business complexity or the dissociation between investors and management teams. Nor has audit kept pace with the opportunity to use technology to support business – and that creates frustration for auditors.

There has been a tendency to leverage technology to automate the checklists and rules that govern the way audit has been done, rather than to ask whether there are fundamentally different ways of approaching the audit. Automating the old ways are unlikely to mitigate the risk of business failure caused by the increasing complexity of businesses, a risk that COVID has exacerbated.

Why do we, as an industry, spend so much of our time ploughing through endless checklists and verifying run-of-the-mill invoices, rather than actively seeking the key areas of business vulnerability? Why spend time manipulating data to identify outliers rather than investigating those outliers and understanding their business implication? At what point does compliance get in the way of the talented people in our industry from providing value and in doing so, fulfil their duty to businesses, shareholders, and the wider public? 

There is an opportunity for auditors to avoid the daily frustration of working through a checklist and instead leverage their high level of knowledge and skills to interpret the key financial information of a business. One key barrier to this critical change is the resistance to invest in new technologies and the slow adoption of a risk driven, agile way of thinking about the work that needs to be done in order to provide assurance.

New Economic Imperative

In some ways, COVID-19 is acting as a catalyst for this essential change. Business models have been turned on their heads and revenue streams radically transformed. New risks have emerged, and many balance sheets are unrecognisable. COVID-19 has accelerated trends towards greater digitisation within businesses and will exacerbate problems with auditing complex organisations whose value is largely composed of intangible assets and human capital. CFOs need to rapidly understand the new business landscape and identify priority areas of risk.

How confident, for example, are firms 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 operational challenges. These challenges are laid on top of worries around valuing assets which are increasingly fluid and hard to pin down.

Data Driven Value

Companies need rapid identification of areas of unexpected activity today. Auditors are perfectly placed to support companies and provide this vital insight. Timely identification of risk can deliver real business value, and the audit industry should embrace this role. Sophisticated machine learning and artificial intelligence techniques can enable auditors to rapidly surface business risk by identifying areas of unexpected activity. Critically, unlike humans who typically see what they expect to see, intelligent technologies allow the data to speak for itself. The algorithms will simply work through the data, finding patterns and revealing insight that would be impossible to discover manually.  

Replacing checklist driven investigation with a risk-driven, machine learning enabled investigation provides the foundation for a new level of audit confidence as well as business insight. Whether it is identifying errors, flagging unexpected trends in invoice realisation or revealing potential employee fraud, audit firms embracing a data driven, risk focused methodology can rebuild corporate faith in the quality and value of the audit process.

Critically, it supports a long overdue shift away from the annual cadence of audit, recognising that although annual audits can do the job, they are often too late to be relevant to key stakeholders. Companies have steadily moved from quarterly to monthly, to daily reporting and often real time data for their internal reporting. There is no reason, beyond characteristics in the audit market, for this to be the case for external audits as well. Companies require rapid insight and auditors must consider how their work for clients can be more timely, more valuable. From developing new service lines to reconsidering operating models, there is a significant opportunity to deliver greater value to the world economy through enhanced, timely business understanding.

Innovation and Differentiation

For auditors, this shift in approach provides the opportunity to redefine audit and discover a new role in the market. This is not about leveraging robotic technology to automate audit processes and reduce the workload. It is about providing auditors with a way to effectively address the challenges and complexities of modern business models and deliver real value. In some cases the data may reveal the need for more work; in others, the audit process may be streamlined. Risk based audit moves away from a one size fit all approach to one that truly reflects the state of each individual client’s business. Audit data becomes relevant, meaningful, valuable. 

Technology, however, is only an enabler. While the market dynamics of audit still remain under review, firms need also to shift the focus and pay far more attention to those companies that are complex or high risk, companies whose fortunes affect the performance of thousands of pension plans and individual investment portfolios. Those audit firms that are actively pushing to deliver more value to clients, to improve the quality of, and confidence in audit and minimise risk across the board are at the heart of what should become an inexorable shift to this new audit model.

Author

  • Stuart Cobbe

    Stuart is the Director of Growth, Europe at MindBridge and is responsible for helping finance professionals embrace data driven decision making through AI. His role explores the ways that machine learning and data analysis can gather insight and assurance whilst cultivating the right set of skills so that auditors and accountants can offer leadership in a data-centric world. After graduating with a Bachelor of Science in Politics & Economics and a Masters in International Relations, Stuart has worked in a number of different financial and auditing roles and has completed the ICAEW Chartered Accountant qualification, one of the most advanced learning and professional development programmes available. The ACA qualification is highly valued around the world in business, practice and the public sector. Prior to his role at MindBridge, Stuart was Board Member at Helpful Engineering, Founder of Brevis and Data & Analytics Manager at Moore Kingston Smith.

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