European CFOs Must Implement AI at a Faster Pace
CFOs of European firms are unanimously convinced that artificial intelligence (AI) has the potential to have a strong impact on the financial department. But when it comes to implementing this technology, they are significantly lagging behind their American counterparts. In fact, many American firms are already comprehensively using data analysis and machine learning to guide and support their strategic decisions. However, this isn’t necessarily the case in Europe, says Kristof Stouthuysen.
Machine learning and AI can have huge benefits to the financial department and could allow companies to create and tailor their models based on the data they have collated. This technology can dissect the data inputted and try to perceive the deviating patterns in this – a good example already prevalent in the financial industry is the analysis of payment behaviour in fraud detection. Machine learning is able to signal that someone is making payments from two completely different locations in a short period of time, which can indicate a fraudulent purchase. Though this is a common example of machine learning in finance, there are a huge amount of other significantly beneficial ways that AI and machine learning could be implemented – so, why are European firms not applying this as eagerly?
Well, there are a number of reasons as to why this could be the case, the most common being that there is simply a lack of know-how in this area. Accountants and finance professionals, of course, have extensive knowledge and expertise in the field of accounting standards, risk management, investment analyses and controlling, but not in the area of emerging technologies, machine learning or AI. Therefore, those in the finance department are not able to simply implement this technology and must look to external parties to help this transition – which can be timely and also a deterrent. But this is unjustified, as many CFOs could quickly master the basics of machine learning through training and not necessarily take on these roles themselves, but at least understand the technology.
Many CFOs could quickly master the basics of machine learning through training and not necessarily take on these roles themselves, but at least understand the technology.
Not only is there a lack of know-how, but there is also a lack of time for a CFO to implement this technology, or find a partner who is able to do so. A CFO’s job role usually focuses on value creation and protection, and transactional tasks too. Only once less time is spent on these is there the possibility for CFOs to focus on strategic tasks, such as implementing new technologies. CFOs tend to be extremely time-pressed individuals, until they free up time to focus on these strategic areas, or employ someone in the finance department to do so, it is likely that the option of applying these technologies will not be possible.
Infrastructure, company culture and the risk and governance surrounding implementing this technology can all have a profound effect on the possibility of companies doing so too. Not every company has the designated ICT infrastructure to store, analyse and structure data, and of course, the extra computing power and server capacity that are also required to do so. In a company where the financial department culture is not data-driven, it may be hard to convince the necessary actors of the importance of implementing data in financial practices; the management needs to support this area of focus. The risk and governance related to data issues is also a major concern for companies, whether it be related to security, GDPR or compliance, which means that many firms may be reluctant to pursue this avenue.
All these barriers that a CFO may be faced with when trying to implement data analysis and AI into their practices can, however, be overcome. Whether it is redistributing money to focus on technology in finance, employing external firms or internal actors with knowledge of the technology, or investing in software and infrastructure which can facilitate data analysis, these all are worthwhile tasks for a CFO to implement in order to benefit from this new technology.
In this pursuit to apply AI in the finance department, the CFO should continue to play an overarching role in the company, but also add advanced automation and machine learning to their list of tasks. There is a need to have employees that excel not only at accounting and financial knowledge but also at the ability to work with new technologies, including AI. A data-driven finance department will better position itself as a strategic business partner.
In this pursuit to apply AI in the finance department, the CFO should continue to play an overarching role in the company, but also add advanced automation and machine learning to their list of tasks.
In fact, there are four concrete applications of AI that could be seen currently in the finance department. For example, these technologies have the ability to quickly evaluate potential investment opportunities, by scanning and consulting annual reports and management reports of the companies on the list of their potential investments. This can help companies to quickly understand possibilities of profit growth in these investments and allow them to come to a much quicker decision on their potential investments.
Machine learning and AI can also be implemented to analyse mass social media messages regarding the company’s practices, products or services or current prices. This will help companies gather mass opinions of them in a short space of time and give them the ability to understand how to better streamline their financial services and offerings in the future too.
This technology can also predict future business issues as well, by mapping the network and history of potential suppliers and collaborators. AI can provide a specific and sophisticated understanding of a company’s public image, which could help the company avoid aligning themselves with companies with the potential to have a negative image, and therefore save them money in the long-term by maintaining their positive brand image.
Every company looks to gain insight into the profitability of its customers, this AI technology can also help companies with predicting the potential reaction to new services and products that they are looking to offer. Therefore, companies are able to understand whether or not these will be financially worthwhile in the long-term, and whether customers will be likely to consume these.
New technologies such as AI and machine learning will have a profound impact on all business areas, including the finance department, and CFOs who look to embrace this as soon as possible will be one step ahead of their competitors. For the future of finance, it is important that the training of financial students and current employees includes a greater focus on technology – how to implement this and its impact on finance. This is something that education institutions like Vlerick Business School have adapted to, offering more and more technology-focused modules in their finance programmes and ensuring that the next generation of CFOs has a strong knowledge of both accounting & finance and technology.