New technologies and the future of accounting

The wide-ranging economic impact of information technology is clear when we think of organisations and markets as information processors. New technologies, such as big data, artificial intelligence (AI), cloud computing, and 5G are leading our economy to a possible Fourth Industrial Revolution. The technology not only brings cost efficiencies to firms, but also significantly changes business models, organisational structures, and the composition of the labour force. Firms are investing heavily in technology related to data analytics for use in areas such as marketing, operations, financial reporting, and internal audit. The International Data Corporation (IDC) forecasts that worldwide revenue for big data and business analytics solutions is set to reach USD 274 billion in 2022, with a five-year compounded annual growth rate of 13.2% (IDC 2019).

Replacement or helping hand?

How will the extensive application of information technology affect the accounting industry? What are the futures for accountants? Is it likely that AI-powered robots will eventually completely replace accountants and do jobs such as transaction verification, asset measurement and detecting abnormal journal entries more efficiently and effectively? If that is the case, we accountants are facing a gloomy future. If, on the other hand, AI will take a long time to reach a level to challenge human intelligence, and will be used as tools to help us make more efficient and accurate decisions, then a critical question is what new skills will we need to learn in order to adapt to this new era?

Nobody can predict the future, but we can be sure that preparation will help us. In this article, we will discuss how two most relevant technologies, AI and big data, are related to the accounting industry, the potential impacts they may have on the future of accounting, and how accountants can get prepared.

AI will take over many accounting tasks

AI refers to the use of computers to do jobs that used to require human intelligence. The concept dates back to the 1950s, when John McCarthy, the father of AI, first described it as "The science and engineering of making intelligent machines, especially intelligent computer programs." In recent years, AI applications have started to appear in more and more business scenarios. Natural language processing (NLP) allows firms to use auto-reply customer support, greatly reducing human workload. Image recognition algorithms produce great performance in areas such as medical diagnosis and virtual banking. And network based algorithms are determining what people see on online shopping websites or social media.

Given the power of AI, many tasks that used to be done by accountants can be done by AI-enabled algorithms or robots. Indeed, many companies are already using basic automated accounting processes. According to Forbes, machines will carry out or streamline tasks and processes such as supplier onboarding, accounts payable, audits, procurement, purchasing, expense management, and customer queries. More advanced applications will follow.

Time-consuming inventory checking can be completed within minutes

In the future, a standardised sales contract will be easily analysed by a customised NLP system to identify the key terms for further information processing. Preparation of routine internal financial reports will be done automatically on a daily basis. Time-consuming inventory checking will be completed within minutes with the help of drones taking panoramic photos. Further automatic analysing and counting will be done with the help of image recognition technologies. And cross-checking processes for internal control purposes can be fulfilled by welldesigned systems that retrieve and compare information across different departments. For instance, the pictures above show cattle pens taken by a drone. The pictures are analysed by an algorithm to count the number of cows in the picture. One can easily see the efficiency improvements such new technology can bring.

Computers can go even further by performing tasks that used to be too costly to implement. Reports describing the key functions of a firm can be prepared on a weekly, daily or even hourly basis, replacing the old monthly or quarterly reports. Bad debt provisions can be analysed on a granular level. Such timely and detailed information can improve the value relevance of accounting information in facilitating business decisions.

The accounting department will coordinate the re-engineering process

The efficiency of daily accounting tasks and processes will be improved by AI-based automation technologies, but this will require a more integrated firm information system as basic infrastructure. The transition from the traditional silo information systems to such an integrated system will not be without pain. The accounting department, as the central functional department, will need to coordinate the re-engineering process. This will require a deep understanding of the entire business model, taking a critical look at the value of current accounting tasks, foreseeing potential future accounting practices and needs, as well as commanding an updated knowledge of new information technologies.

Along with the change of firms' accounting systems, auditing practices will need to be changed too. For example, auditors will need to understand the coding language, or at least the logic of coding expressions to evaluate the efficiency of internal control systems, and to decide whether accounting numbers generated from the system comply with international accounting standards. The traditional sampling practice in auditing process may also evolve toward a full-screening methodology, changing the entire design, implementation and quality control process of audit work.

The scope and complexity of big data will continue to grow

Big data is another growing trend that will affect the future of accounting. Big data refers to data sets that are so voluminous and complex that traditional data processing application software cannot deal with them.¹ With the development of information storage technology, computing power, mobile devices, and wearable devices, we will have access to a much greater range of data with growing volume, dimensions, formats, and complexity. Consider these statistics: Google processes more than 40,000 search queries per second. Facebook users send about 31.25M messages and watch 2.77M videos a minute.² According to IDC, "by 2020 the digital universe – the data we create and copy annually – will reach 44 zettabytes, or 44 trillion gigabytes."³

Real-time information will replace traditional accounting sources

Traditionally, the accounting system has been viewed as one of the most relevant and reliable information sources to help with economic decision-making, both internal managerial accounting and external financial accounting. But going forward accountants will face growing competition from new information sources. Conventionally, a firm's performance as reflected in accounting numbers is one of the most important pieces of information for stock pricing. However, nowadays investors may find that the real-time updated information provided on some e-business websites can provide more timely (though maybe less accurate) projections of performance. One example could be the "search index" information on some social media, which reveals the most popular pop stars/movies/ products, etc. How should the accounting industry embrace such trends and retain its competitive advantage as an information source?

One foreseeable change is that more granular supplementary information will be documented and stored during the traditional book keeping practice. For example, in the payroll process, individual level performance information is calculated and documented usually on a monthly, quarterly or annual basis. In the future, daily or even hourly personal working related information can be recorded and stored for further analysis. Such information can help better evaluate employee performance, improve efficiency, and predict failures in manufacturing processes. To help utilise such information, book keeping practices, flows of information and information systems all need to be re-designed or re-engineered. The Internet of Things, which links, transfers and stores data from computing devices, mechanical and digital machines, objects, animals or people, provides a great opportunity for accountants to keep track of assets and resource flows in a timely and accurate way and may largely change the overhead allocation practices in cost accounting.

Professional judgement will play a more prominent role

With workload released by robotic process, accountants will devote more time to utilising new information sources, improving the quality of professional judgement. They will also provide more customised supporting reports and data analysis to meet the growing demand for better decision-making. One example would be the estimation of bad debt provision. While the traditional practice is to estimate the probability of bad debt using historical records, in the future accountants may use big data to evaluate the credit worthiness of individual customers and better predict the probability of future bad debt. Also, the large volume of big data will allow accountants and auditors to perform different statistical models, or deep learning technologies to predict important economic events such as supplier or customer financial distress, employee crime, financial fraud, etc.

Accountants will learn to deal with unstructured data

One challenge is the use of unstructured data. This is unlike the traditional structured data that are clean and usually stored in relationship-based databases. It takes great effort to retrieve, understand, validate and process the data before they can be used for further analysis. Accountants will need to gain some basic understanding of the techniques involved in dealing with this big data, and cooperate closely with data expertise or scientists as necessary. Instead of focusing solely on data processing, accountants have the advantage and expertise in understanding the business logic of a firm. This allows them to ask valid questions, which is the starting point of meaningful data analytics. More importantly, through modern algorithms such as neural networks, deep learning can identify or construct unspecified features or factors in a predictive model. Very large amounts of data and computing power are required to make effective predictions. These conditions are not always met or are too expensive in business scenarios. Accountants, instead, can use their expertise to help improve these models and make better predictions.

Working in a transformative era

In the near future, we believe AI will become ubiquitous. Though it is unlikely that AI-enabled robots will completely replace accountants, they will substantially transform the accounting industry as we know it. Accountants will need to develop sets of new skills and continue to be resilient, adaptive and innovative to remain competitive and help their organisations navigate this transformative and revolutionary era.