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When thinking of robotics and artificial intelligence (AI), many of us will automatically conjure up images of futuristic robots and applications from sci-fi films. However, the reality is very different. In fact, Robotic Process Automation (RPA) and AI are integral to many businesses, allowing for simple and repetitive tasks to be carried out faster and with fewer errors than when carried out by humans. While most commonly associated with manufacturing and IT industries, AI is also currently in use within the finance sector for stock trading, predicting fraudulent transactions and determining risks.
Thanks to continuous developments, AI and RPA is slowly being integrated into a wider range of financial processes and presents the financial domain with incredible opportunities moving forward. With the power to revolutionise not only the sector but also the roles of those working within it, will all the changes AI and RPA have the potential to bring be welcomed?
One of the major benefits of the implementation of AI and RPA is that it is likely to provide finance professionals, particularly credit managers, with a greater degree of transparency of financial processes. One such process is that of order to cash – a collection of business processes for the receipt and processing of orders and ultimately their payments. This process ensures there is continuous cash flow, and without such a process there could be dire consequences for an organisation's survival. This is one particular area that AI and RPA could be put to good use, allowing for some of the simpler, more repetitive tasks to be automated and for finance professionals to focus only on exceptional cases that can’t be processed by RPA. Additionally, the technology will ensure all financial information is up-to-date and comprehensible in real-time so that finance professionals can focus on analysis and strategy.
This new technology will also make it possible to achieve much more with data that is being collected by finance departments. One such example is performing reliable predictions based on the past. For example, AI can analyse data in software solutions and determine if there are any patterns in order to predict events, such as which customers will fall into payment arrears. This will allow credit managers to determine when action should be taken and whether to approve credit. In turn, this is likely to increase cash flow as finance teams have an increased awareness of which customers should or shouldn’t have their credit approved. Predictions made by AI can also be applied to other processes, such as the invoicing method, as AI can predict which payment method will result in the invoice being paid quickest, and transferring customers to collection agencies.
While AI has been in use for some time, RPA is fairly new to the finance sector with several pilots having been conducted to further investigate how it can be used. While currently unable to carry out more complex tasks or those with many exceptions, RPA has the potential to automate a number of the more tedious but necessary financial tasks, such as processing bank mutations, compiling reports and invoicing. Usually a lengthy and time-consuming process, the use of RPA in invoicing would enable the hundreds of invoices usually dealt with manually to be automatically inputted and processed within the system, saving hours of time usually spent by individuals on the task. Similarly, it would make it possible to automate the processing of mortgage applications with automatic financial advice provided based on algorithms.
Additionally, RPA and AI can enable tasks which have previously been automated to be taken one step further. For instance, these new capabilities enable an improvement in the assessment of a customer’s creditworthiness by using AI to segment customers into groups based on established rules. Until now, this assessment had involved rules that were very black and white, which meant credit managers needed to assess any grey areas. Now, AI can be introduced to make new connections to assess these grey areas – making it easier for informed decisions to be made on credit risks.
Not only would the introduction of RPA and AI in these processes see them speed up, but they would also achieve greater accuracy which in turn would lead to increased quality and lower costs as fewer resources are needed for certain tasks. As a by-product of this accuracy and the automation of tasks, financial professionals will find that they have more time to spend on bigger-picture tasks, allowing them to focus on making a difference to their organisation and customers.
With a marked reduction in the time spent on the more mundane tasks, financial professionals may experience an increased level of job satisfaction as machines take on the more monotonous day-to-day aspects of the role they had historically been tasked with. This, in turn, will benefit businesses as a whole as their employees are able to derive greater insights as a result of their shift in focus.
In spite of the many benefits financial professionals are set to experience, there is a more troubling way in which they could be impacted by RPA and AI with research suggesting that 230,000 finance jobs could disappear by 2025 as robotics take their place. For businesses, there are several ways in which robots ‘out-perform’ workers – for example, unlike humans, robots are productive 24 hours a day, 365 days a year; they never tire and are never sick. Combine this with the fact that robots are also getting smarter and more affordable, and it sounds like they are the ideal ‘employee’. It is therefore unsurprising that some financial professionals are concerned about the wider implications of this revolution.
If, as predicted, job losses occur as a result of the increased use of AI and robotics, it will be up to financial professionals to carve out new roles for themselves. This could see some working in this industry up-skilling in order to work behind the scenes to develop the very technology posing the treat. However, it is important to remember that at this stage, job losses are purely theoretical. In the immediate future new technology presents the financial sector more benefits than it does risks, allowing individuals to relinquish control of some of the more mundane tasks they currently undertake. In short, AI is about aiding workers to do their jobs better, rather than about replacing them.
Ultimately, AI and RPA will be able to provide support at all times and make it possible for finance professional to take decisions in a more efficient and more effective manner, decisions that benefit the organisation as well as customers. Despite the concerns of those working within the financial sector, a revolution is coming. Yes, change is a risk but failing to change involves an even greater risk. Organisations that do not adopt new technology, and thus fail to innovate, will be caught up by the competition. Instead of fearing change, workers should revel in the thought that thanks to AI and RPA, repetitive and manual tasks, which no finance professional secretly looks forward to, will be consigned to the past.
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