We use first and third-party cookies for analytical and statistical purposes and to show you personalised advertisements based on a profile compiled from your browsing habits (e.g. pages visited). For more information, click on our Cookie Policy. You can accept all cookies by pressing 'Accept', you can reject all cookies by pressing 'Reject', or you can customize your choice by pressing 'Manage'.
Strategy and innovation
Artificial Intelligence for CFOs.
AI has applications for every level of a company, from machine learning to data mining and management tools in the cloud with software as a service.
Finance departments have been on the front line of the pandemic and ensuing crisis. One could say that they have moved from the back-end to the front-end by taking over the strategic role of the Chief Financial Officer (CFO), rather than just focusing on their traditional technical expertise. Businesses are now facing unprecedented levels of stress and their sustainability has depended on the speed with which decisions have been made and resources diverted to digitalisation, with the CFO at the centre of operations, while the business seeks to arrange national and European loans and other support measures. A human and business intelligence effort where AI has finally knocked on the door of the financial services sector.
Artificial intelligence (IA) has been dubbed the new electricity because of its potential to light up a new economy. It can be applied across all levels of the company, through angles such as machine learning or data mining and management tools in the cloud with software as a service.
In response to the power that AI has been amassing, the European Commission has been working towards an Artificial Intelligence Act since April 2021 and is looking to turn the continent into a leading hub in the new knowledge industry.
Are finance departments already using AI?
According to a PwC survey, 68% of CFOs plan to invest in the next year in digitising their processes, from working in the cloud to making further progress in data mining. How IA is perceived is another thing entirely: only 14% of companies have made it part of their finance department, compared to 36% that choose to use it in their product development department or 24% in customer service, according to a report by EY and Microsoft.
Of the 86% who confess to not using AI in their finance and accounting departments, a good proportion of them do use it on a daily basis as part of their business, even if they are not aware of it, because their choice of software typically incorporates one or more practical AI features.
It is like a Netflix user being asked if they have signed up for an AI service. They would say they have not and that they have arranged an entertainment service. They are not aware that AI assists the platform day in, day out to learn their usage habits, send them new offers, choose the best day to remind them to renew their subscription, predict when their card will expire and detect from the usage patterns if someone else is using the service with the same password.
Artificial intelligence is out there, even if we can't see it. It doesn't like to show off or shout out its presence: it is simply there for us.
Let's look at some examples of how AI is changing the daily lives of finance departments and, by extension, companies.
Data as a decision-making factor
Data is king
Artificial intelligence helps the CFO and the company make decisions. The finance department is naturally the area that handles the most critical volume of data. And, as the catalyst for all this information, the CFO is responsible for delivering it in the highest quality and with the greatest predictive and prescriptive power.
From static data to dynamic data
Thousands upon thousands of pieces of data arrive on the CFO's desk each and every day, both structured (numbers) and unstructured (images, videos, texts). Artificial intelligence helps us shape them and to convert pixels and semantics into numbers. AI provides the first interpretation and processing of the data to keep the business running.
The magical year: 2024
When will we see a return to the highs of 2019? Some reports point to a major recovery in 2022, by which time we will be able to lure more tourists out of their source markets, but we will not be hitting peak figures before 2024.
Data culture permeates the entire organisation
While this may seem obvious, it is not always the case. The finance department knows all about this and therefore bases its recommendations and decisions on data science, not as a snapshot but as a driver of growth.
The beauty of intelligence
AI-based data collection, sorting and presentation systems must be delivered in an understandable, simultaneous and visually appealing way throughout the entire organisation. Most software-as-a-service tools already include this out of the box.
AI as a driver of change in finance departments
New technologies have been part and parcel of the daily activities of a CFO for years now. Hardly surprising since the finance departments were the first to make the leap to process automation. They were pioneers in abandoning paper-based accounts and diving into the world of data. But in recent years, other departments have moved faster in implementing AI, from marketing to talent management.
Financing must travel at the same speed as the business. This has been demonstrated time and time again during the pandemic. It is time to learn from experience.
Taking the lead
Moving from back to front. No one is saying that the departments should no longer provide support, but they do need to step up and take the lead. They have proven to be the brains of the business, especially during the COVID-19 crisis. They have a broader, more horizontal view of all areas and centralised access to all information.
Reducing complexity
Information is now flowing horizontally throughout companies. Whoever succeeds in simplifying and democratising access to financial information will win. The CFO must be the catalyst for that change.
Planning each day
Things are changing so rapidly that we need to react and make investment decisions at a speed that was next to unheard of three to five years ago. Planning times are now much shorter and planning ahead in years seems to have gone out of fashion. AI is the tool we can use to speed up our analysis and improve our foresight.
Throttling financial decisions to the speed of the business
Products are now being launched in record time, though questions such as performance and uptake needs to be gauged in real time. It is here that the CFO plays an important role in deciding on whether to keep investing or pull the plug. They need to manage a huge amount of live data, control costs, measure profitability and check the impact on the bottom line, all in real time.
5 keys attributes of Artificial Intelligence tools
1. Scalable
Everything is changing so rapidly that a company's ability to react is sometimes measured in hours, no longer months or years, and diversification is now the way to go. I must have access to tools that can grow alongside my business and adapt to new markets and lines of business.
2. Understandable
If we find that AI is making life difficult for us, it's because we are not using it properly. The new intelligent software must be adapted to different layers of presentation and different levels of understanding, so that it is properly understood and adds value throughout the organisation. The information it generates for an operations manager is not the same as for a marketing manager or CEO. And team training is essential.
3. Speaking the same language
Many companies suffer from something known as the Tower of Babel syndrome, where they have various tools that do not work very well together as a result of tactical decisions that were made without a roadmap. This problem is now hampering companies that want to make the leap to AI. We are moving towards a software-as-a-service world. It's much like our mobile phone: apps are updated and adapted to the user, and not the other way round.
4. Tools
It might seem obvious, but it is often worth asking ourselves what it is we really need. Is the new tool helping me to spot deviations in the accounting entries? Is it helping me to plan, budget, or predict sales?
5. Integrated
The problems that can arise from the implementation of machine learning or new software are often structural in nature: applying disruptive technologies to old processes causes dysfunctions. AI must be accompanied by a change in processes, and once again team training is key.
Preventing scenarios and risks with intelligence
We have gone from analysing monthly in arrears or planning ahead for a whole year to analysing every single day and every single week. While business plans can still be four- or five-year affairs, there are also three-month versions now. Agile methodologies were born with the aim of bringing new products to market by shortening development, production and marketing times. They also require much more prescriptive and rapid profitability analysis and forecasting.
AI frees the CFO from traditional functions that are now automated, enabling them to focus on more strategic concerns. It raises their performance and lets them concentrate on high value-added tasks, bringing them closer to the operating side of the business. One of these tasks is to build better predictions of the future from data, to become faster in operational terms, to reduce costs and to control risks.
Today's management teams are asking the CFO to be more predictive and to know —in real time based on up-to-date data— what the company will look like in the short, medium and long run.
AI means making data panoramic and in continuous motion rather than staring at the past and providing a still image of the data. Intelligent software learns from our experiences and those of other companies to provide me with better solutions and smarter predictions. Some examples:
Measuring business risks in all its facets
From market research to supply chain behaviour or pricing. Financial intelligence is now of paramount importance amid the microchip and international shipping crisis.
Calculating financial risks
Potential partnerships can be assessed through automated processes. Machine learning has proved its worth as an instrument for measuring financial risk by being able to process a huge quantity of data and indicators that we would never be able to process as accurately were we to do it manually.
Preventing non-payments
Thanks to machine learning we can anticipate customer non-payments and defaults. Just as AI helps us to see how our customers behave, it also anticipates and provides valuable information on how they pay, on their habits and repetitive behaviours, and on any financial hardship they may encounter down the line.
Preventing fraud and other unlawful activities
AI has become an ally of banks and businesses alike, in spotting unlawful activities and helping to prevent money laundering by analysing millions of pieces of data per second and identifying possible signs of fraud. It is interesting to note that we, as a company, are also being monitored and analysed by AI. Investors, insurance companies and lenders use AI in risk management and credit rating.
Examples of AI applied to finance departments
Bank reconciliation
While this has been an automated process at companies for many years now, with modern machine learning systems we can make the software learn and detect more intelligently —and according to our needs— what data we can extract and enter automatically and what data will require more involvement from our team. By analysing the historical variables and behaviour of a customer, a market or a point of sale, we can predict their future behaviour: the tool does this by learning from experience and finding hidden patterns that we would have a hard time spotting with the naked eye.
Financial chatbot
Through this system, which relies on AI techniques, the organisation's employees can now resolve a multitude of financial questions and doubts, meaning that internal services no longer have to get involved and sort them out manually. How to find a particular cost centre or where to enter a purchase order, for example.
Technology is a tool that expands the capacity of our senses. It does not replace them, but enhances them. While the telescope allowed us to see further and the wheel let us go faster, AI saves us time by anticipating the future.
Its importance has led finance departments to incorporate more transversal profiles not quite so closely related to accounting, such as computer scientists, analysts and mathematicians.
COVID-19 has put companies around the world to the test. And more specifically their CFOs, who have managed to keep the business afloat not only by shielding its finances, but also by relying on forward-looking scenarios to make quick decisions to minimise the damage.
They have achieved this through ingenuity and by speeding up processes that used to take years and overcoming the challenge of accessing new forms of financing and workforce structuring options.
In the mid runwe need to learn from experience and get used to a scenario of greater uncertainty and volatility. In the short run, we are facing a possible adjustment of interest rates due to an unexpected rise in inflation and supply problems. It is now more important than ever to have technology that saves costs and helps our business grow. It is time to take those robots we have created and get them working to extend our capabilities.
