New technologies set to power the audit
New and disruptive technologies are emerging at a rapid pace. Blockchain, the cloud, robotic process automation (RPA), digital labour, machine learning, deep learning, quantum computing, natural language processing (NLP) — all of these have huge potential to change how a business operates.
These technologies will have implications for an audit in the future, too. The impact they will have — and are already having — can hardly be overstated.
In the analog world where accounting was done with manual tools like physical ledgers, the auditor would validate processes and transactions using statistically valid sampling or similar techniques. In today's digital world, where data is proliferating across digital networks and systems, we are bringing new capabilities to mine the mountain of data to identify audit risks, highlight anomalies and outliers, and focus on riskier and more judgemental transactions – resulting in a higher quality audit.
Already, new technology is dramatically enhancing the analytical power of our audits. Using RPA, our firm can analyze 100% of certain datasets through various lenses. This means quickly identifying the outliers that need further examination. For example, recently an audit engagement team analyzed a complete set of about 250 million transactions, isolating 50 to 60 that were identified as outliers and brought these forward to the organization for an in-depth discussion which provided insights into their business.
On top of RPA processes, we are also applying machine-learning techniques where complex algorithms can scan information, model it against thousands of assumptions drawn from external scenarios and highlight risks and insights. This predictive analytics is a step towards deep learning where, in the future, the application will be able to 'think' for itself, learn from the results and run more scenarios and tests accordingly.
Machine learning (sometimes known as cognitive automation) and deep learning (or artificial Machine learning) is a more 'intelligent' form of technology than RPA as it uses algorithms to analyze data and make correlations and predictions (with human oversight).
Deep learning is where the technology appears truly intelligent as the machine may learn from its own experience, teach itself how to perform a task or analyze it, and can improve its own performance or effectiveness. It is as though the technology has a brain.
On a spectrum of technological advancement, RPA is the most basic, machine learning is more sophisticated and deep learning is the most sophisticated of all.
One of the critical development areas in the coming years is the analysis of unstructured data. Structured data — found in spreadsheets and ledgers — can already be comprehensively analyzed using D&A and automated capabilities. But more than 80% of data today is in unstructured formats such as contracts, emails, PDFs and other documents.
The marriage of natural language processing technologies allows machines to read those unstructured data sources and create digital files that can be compared to the transactional records. The speed and effectiveness of such procedures will allow auditors to move quickly through those transactions determined to be supported and those that are not, allowing even more time to focus on areas requiring more critical judgments and estimates.
A key battleground is to develop digital assistants that can read this data and identify key information. Having a bot, for example, analyze the accuracy of one of those unstructured files. The development of NLP capabilities to read emails is another example. By using the processing power of intelligent machines, we can use correlation theory to extract data from unstructured sources.
But the future of technology is by no means only about intelligent tools to analyze data. We are seeing momentous changes in the way data is hosted — in the cloud. While some organizations may prefer to keep their data in on-premise servers, there is no doubt that the move to the cloud is likely to continue to grow, offering greater flexibility, processing power, and functionality.
One key issue, regardless of how powerful new technology has become, is accessing the organization's data. In the future, we could see the development of technology to enable more seamless transmission of data from the organization to auditors. Enterprise resource planning (ERP) systems tend to be customized by each user company, and they may have multiple systems and legacy systems — so streamlining them to aid the ease of data extraction and transmission is likely to be in every party's interests.
Running alongside all of this is the development of an exciting new technology system — blockchain. With the potential to create an immutable record of transactions, blockchain could have wide applications, from such things as trading derivatives, inter-firm payments, loyalty points, and identity to supply chain and logistics in businesses more widely. With access to the blockchain, auditors will be able to review all the transactions across it; it could change the work auditors do in verifying information — and create new responsibilities such as evaluating that the blockchain is reliable and accurate.
"Embracing a rapidly-advancing new technology is not easy but as seen recently, Canadian companies are beginning to adopt blockchain in a very serious way," says Paritosh Gambhir, Head of Blockchain and Partner for Financial Services at KPMG in Canada. "For companies not in this space yet, I fear they may already be behind. Blockchain will not just disrupt organizations; multi-party processes, such as supply chains, will also be greatly optimized and accelerated through this technology."
With so many disruptive technologies emerging on so many fronts, it's clear that now more than ever safeguarding data and ensuring privacy must be a top priority for organizations.