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Building an intelligent finance 4.0
Earlier this year, an Oxford Insights study ranked Singapore first globally for Artificial Intelligence (AI) readiness. This reflects the country's ongoing Smart Nation initiative, where efforts to build up an AI sector and support the workforce in leveraging new technologies are in full progress. The launch of the Model AI Governance Framework by the government, which seeks to guide private sector organisations on how they use AI solutions ethically, is testament to this effort and is one of the first of its kind globally.
The upsides of AI as a technology are plenty. AI can help businesses to make smarter decisions, improve business productivity and outcomes, and enhance customer experience. At the same time, many are anxious about the job displacement impact that AI may bring.
Similar to many business functions, the finance function is not spared from the impact of the technology. In fact, finance leaders are in a prime position to bring AI to the business, by virtue of how they sit at the intersection of the most useful data to any organisation, such as operating costs, receivables, and the financial performance of each business unit. In addition, many finance leaders also assume compliance roles and have responsibility for the organisation's financial and regulatory requirements.
Finance leaders are increasingly asked to support the business in its growth plans and play a direct role in driving revenues, and they understand the demand. Almost three-quarters of finance leaders in the 2018 EY corporate reporting survey said that AI will have a significant impact on the way finance drives data-driven insight, and that it will be the critical technology for the finance function in the future.
Technology-driven efficiency and insights
The jury is still out on when, if ever, the world will develop a general-AI capable of competing with humans across a broad range of cognitive and sensory tasks. However, AI already offers an advantage in both efficiency and effectiveness for single-domain activities, where AI systems are designed such that their expertise is confined to a single task. For example, reading and processing a document or spotting a fraudulent transaction.
These types of tasks form a large portion of traditional finance work that involves capturing data, sending reminders and responding to basic queries. When AI is combined with technologies such as Robotic Process Automation (RPA) and applied to organisational workflows, organisations can realise operational efficiencies at scale.
The time made available through AI-enabled automation will allow finance professionals to shift away from repetitive processing work towards playing a more value-adding role in the organisation. However, the value is not limited to purely additional capacity.
Through the automation of manual processes, the finance function can move away from focusing on documenting the past such as recognising revenues, auditing costs, or monitoring compliance. Using the rich collection of operational and financial data that becomes available, which AI can consume to produce analysis and insights, finance professionals can now better identify underlying patterns in data, predict scenarios and improve business outcomes.
For example, when AI-assisted analytics is combined with the finance team's deep understanding of an organisation's spending patterns, they would be able to provide timely, accurate and valuable recommendations. Armed with these insights and a real-time view of an organisation's financial position, they can then help to influence cash flow and negotiate preferential rates. As finance professionals weigh in on providing strategic input into decisions up to the board level, they are stepping up to provide greater strategic value to the business.
Human-centred skills development
To remain effective in their evolved roles supported by AI, finance professionals need to acquire new skillsets such as data analysis and interpretation beyond traditional finance and accounting skills. Additionally, they will need to acquire strategic awareness of new technologies to identify opportunities and work with data scientists to realise value.
Next-generation finance roles will be less process-driven and put the interpersonal and commercial skills of finance professionals to the test. In fact, these "soft" skills could be the key factor in determining whether finance professionals are successful in stepping up as effective finance business partners.
Communication skills, for example, directly impact a finance professional's effectiveness in convincing senior management to act based on their data-driven recommendations.
Looking ahead, the digital finance professional of the future is expected to be a more enhanced human version of its previous self when AI technology augments human intelligence. This requires organisations to make strategic investments and effectively manage implementations of AI technology, while concurrently training finance teams to acquire new skills and knowledge.
The synthesis of talent and technology is key to delivering the vision of a smart people and smart technologies working hand-in-hand to deliver better business outcomes. Finance leaders who seize the opportunities of artificial intelligence will not just be transforming the business, but also the scope, responsibilities, and power of their own jobs.
The authors of this article are David Ashton, EY Asean Intelligent Automation Leader, and Kirsten Kerrigan, Manager, Intelligent Automation, Advisory Services, both from Ernst & Young Advisory Pte Ltd. The views reflected in this article are the views of the author and do not necessarily reflect the views of the global EY organisation or its member firms.
This article is part of a series in collaboration with CPA Australia to share knowledge on accounting, business and finance issues.