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Here are some key findings from a new report on AI:
- Machine learning is becoming more relevant for many organizations globally, with 24% already having initial discussions or exploring concepts
- Huge opportunities exist for better business intelligence and across a range of activities carried out by accountants
- Adoption of machine learning needs to be based on legitimate business need rather than just wanting to be seen as using AI
- Ethical challenges lie ahead – accountants need to align professional competence and due care with AI and machine learning
- 63% of respondents in Singapore say that machine learning will become a reality in three years’ time
The findings were published in a new report from ACCA (the Association of Chartered Certified Accountants) Machine learning: more science than fiction, which highlights how new tech developments have a massive potential for the accountancy profession. The report focuses on machine learning, which is the ability of computers to ‘learn’ and make decisions or predictions based on analysis of large sets of data.
Narayanan Vaidyanathan, the report’s author and head of business insights at ACCA, said: “Machine learning is a critical area of development for accountants. Looking ahead it will be crucial to understand its value and benefits, as well as the ethical challenges it presents. In all this, the starting point has to be a legitimate business need with a clear understanding of what it can bring to the organization.
“AI and machine learning can add value to the work accountants do – from generating valuable insights for business decision-making, to fraud detection, risk assessment, understanding complexities in taxation and also with more effective non-financial reporting. So the accountancy profession needs to understand how AI and machine learning works, especially given its role in influencing the trust we have in the decisions of these systems.”
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Reuter Chua, head of ACCA Singapore, added: “Singapore prides itself on its tech capabilities, and is a thriving global tech hub. But when it comes to AI, accountants are trying to see through the hype to understand the realities. As with all technology, with power comes responsibility and in the case of machine learning ethical considerations are never far away. Accountants need to consider and manage potential ethical compromise from decision-making by algorithm, such as the risk of bias in the data set that feeds them and the issue of accountability for decisions made.”
The results for Singapore show that 27% are having initial discussions or exploring concepts of machine learning, compared to 24% globally. 6%, one of the highest percentages compared to other markets, are at advanced testing stage, with ‘go live’ in three to six months, and another 6% are at full production mode dealing with live data.
The report also found that 35% of those surveyed in Singapore have no plans to adopt machine learning in their organizations, while 13% are undecided about it.
Locally, the main barriers to adopting machine learning are lack of skilled staff at 57%, with 48% citing cost as a barrier. Nearly a fifth admits they see no clear benefit from using machine learning.
The report emphasized that at a minimum all finance professionals should know how AI is evolving and be alert to how the developing capabilities could overlap with their impact on their roles.
To prepare for the digital future, ACCA already examines a range of digital topics within its Masters level ACCA Qualification. It has also enhanced the digital content across many of the exams for students, while also ensuring digital is weaved into members’ continuous professional development.
Reuter Chua concluded: ‘Machine learning’s entrance into the accountancy mainstream is a huge opportunity here in Singapore, but also globally. This is an area where professional accountants have the chance to develop a core understanding of emerging technologies, building their digital skills alongside their communication skills so they can explain the results really well. They can then truly benefit from the ability of technologies like machine learning to support them with intelligent analysis of vast amounts of data.’
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