In a series of articles, John Colthart examines how artificial intelligence may transform aspects of accounting by processing vast amounts of client data to report on behaviour, trends, and anomalies.
This week he looks at how AI is already helping auditors by offering advanced methods for understanding ledgers, detecting material misstatements and reporting on risk to clients.
It’s hard to read the news or scan social media without some mention of artificial intelligence (AI). It’s all around us and already affecting many aspects of business and our daily lives. From voice assistants on mobile phones to self-driving cars, AI plays a vital and evolving role in how we understand and interact with the world around us.
The question is, what does AI mean for auditors?
Background on AI
Over 60 years ago, the first AI projects focused on tasks such as language translation. At the height of the Cold War, the US government funded a project to determine whether a machine could translate between English and Russian, but progress was limited due to the available computing power of the day.
More recent advances, such as IBM Watson defeating a Jeopardy! champion in 2011 and the AlphaGo program beating a human Go player in 2015, have brought us closer to thinking computers. AI and its associated technology, machine learning, have come to understand and take actions on the world at large. But they have not reached the point where human nuance and inspiration are replaceable.
AI is transforming the accountancy industry by processing vast amounts of client data to report on behaviour, trends, and anomalies. For auditing, AI offers advanced methods for understanding ledgers, detecting material misstatements, and reporting on risk to clients.
How AI helps auditors
Artificial intelligence automates many tasks that were previously done manually, such as ingesting data, and it analyses 100% of the dataset without requiring a human to create tests, write scripts or remember all the rules.
Key to the future of audit is that AI is changing the definition of reasonable assurance by understanding the entirety of the ledger and identifying anomalies based on risk, rather than rules. With risk-based assurance, transactions are flagged for investigation based on how they deviate from the data set, such as unusual payments or activities that would not normally be caught by traditional testing practices.
While humans rely on judgment and random sampling, which can be time-consuming and prone to missing items, AI rapidly sifts information to reveal risks never thought of before. AI-based systems are also continually learning and adapting to the data. As more information is processed, AI analyses secondary data and cross-correlates with the support of hundreds of variables.
AI also reduces the amount of work on both the firm and client side. By having complete ledgers ingested and analysed, with little manual effort, the need to go back and forth asking questions of the client is minimised. Auditors are free to explore and dive into details as they wish, providing a richer financial picture than ever before.
The impact of AI on the workforce
Will AI replace accountants? The answer is definitively “no.” It cannot replace the experience and judgment of auditors, nor can it understand and manage the relationships between firms and clients. AI works alongside people, automating and accelerating large and complex data tasks, and it assists with decision making when it comes to identifying misstatements and determining risk.
It is transformative technology, and therefore any firm must carefully consider their adoption strategy and timelines. But AI is already improving the scope and quality of engagements and delivering a greater level of assurance for many firms across the world.
It’s imperative for firms to investigate what AI brings to the table and decide their best path. The question today is whether to stick with traditional tools and practices or embrace what AI has to offer right here and right now.
About John Colthart
John Colthart is General Manager, Audit and Assurance & V.P. Product Management at MindBridge Ai. He strives to lead clients to effectively use analytics to change the course of their business
.John has made clients successful in every major market worldwide during his 17-year career in technology, leading world-class sales and professional services organisations.
This started after his departure as a corporate finance and accounting practitioner in 2000 so he could grow a startup to over 425 employees and exit to IBM with the role of VP Sales Operations in 2010. During his stay at IBM, John held global roles running sales enablement, offering management and design leadership within the IBM Analytics division.