A whopping 41% of finance professionals expect big data to be the gamechanger within the industry.
The FinTech Barometer, Onguard’s annual finance survey, shows for several consecutive years that the availability of data is of great importance to organisations. In as many as 95% of companies, data plays a role. Graydon research, for example, shows that companies that use big data in their decision-making and business processes perform 20% better than those that do not. Not surprisingly, 41% of finance professionals expect big data to be the gamechanger within the industry. So developments in new technologies and data acquisition and storage are moving fast. So fast in fact, that 57% of finance professionals expect financial services companies to be transformed into IT companies in 10 years’ time. This and the importance of big data within an organisation are possible explanations why CFOs and other finance professionals expect to need to develop data analysis skills in particular in the future.
However, according to Onguard, big data is more than just a trend. It is important that finance professionals understand how big data can help them in doing their jobs. Seeing available data only becomes truly valuable when it can be converted into insights. Although big data analysis is still a distant concept for many finance professionals, it is the tool within organisations that offers insights. And leads to better performance and ultimately better customer service.
The value from analysis
In addition, big data helps in gaining insights into processes and information flows. The value of big data is in analysing it. That is precisely what opens up new possibilities. As a finance professional, you can use the insights thus gained to introduce new business models or, for example, to tap new markets.
Using big data, you can better assess (financial) risks. You quickly gain insight into how the organisation is doing. With the help of big data, you can better assess risks involved in providing financing and insurance. You can also increase the returns to be achieved thanks to big data. When your organisation makes optimal use of big data by establishing links, you can work more efficiently and reduce costs.
From descriptive to prescriptive
Imperceptibly, we have been working with data for years, that too is nothing new. But by combining lots of (un)structured data from different sources, it is possible to use the data as a basis for informed decisions and predicting customer or debtor behaviour. This is what we call ‘big data’. The use of big data has three dimensions and, of course, we ultimately want to move towards the third dimension. This is where you make a real difference as an organisation. Read further to see which dimensions are meant by this.
- Descriptive: or the descriptive use of big data. The amount of data available makes it possible for a finance professional to actually look at past and present. In this first phase or dimension, the use of big data is quite flat and descriptive.
- Predictive: the second dimension is predictive capability. Using the descriptive data of yesterday and today, a payment pattern can be identified. Based on this, it is possible to predict what might happen tomorrow. If this is possible, the final dimension is close at hand.
- Prescriptive: the third, final and most interesting dimension of big data is the prescriptive, or determining, capability. The moment you can predict that a debtor is going to pay late or not pay, for example, it is smart to take action. This is because it is then possible not to fix things afterwards, but rather to act in advance. Herein lies the power and defining ability of big data.halving, therefore. Is it then that the technology is still not valuable for the order-to-cash process? On the contrary, it has actually proven to be terribly valuable and is, in fact, being widely adopted. With simple ‘if-then’ rules, numerous repetitive actions are already automated. This is already embedded in the technology even before it reaches the financial professional’s workplace. As a result, the latter is completely unaware of it. In fact, RPA is already transforming the order-to-cash process today. And it is proceeding so naturally that finance professionals do not notice it.
What does this mean for the credit manager?
Consequently, the majority of finance professionals (88%) expect their departments to be unable to do without big data within two years. But what does this mean for the credit manager? The advent of big data raises many questions among credit managers when it comes to their jobs. The FinTech Barometer also shows that 42% of them expect big data to have a major impact on employment. And that makes sense. Jobs are constantly changing and especially when big data can ensure that certain risks can be anticipated far in advance. It’s going to help customers avoid payment problems and this in turn reduces Days Sales Outstanding (DSO) and increases cash flow at organisations.
Impact on employment
More than half of CFOs (57%) therefore expect big data to have a lot of impact within finance, this is especially true for current processes and employment. One in three CFOs see big data as a threat to employment (34%). Trends such as robotisation and Artificial Intelligence (AI) are also on the minds of finance directors. Indeed, 43% of them expect AI to have a big impact on employment and more than half of CFOs (52%) see robotisation as the biggest threat to jobs in the Netherlands.
Big data and order-to-cash
In 2021, 36% of finance professionals expected big data to have the most impact on the order-to-cash process, followed by 29% who thought the same of artificial intelligence. The development of these two technologies is still at the top of the agenda now, which is not surprising. Because in the order-to-cash process, unlocking data is soon valuable; it allows you to predict how a particular journey is likely to go. For example, you can deduce whether it is advisable to use a bailiff with a particular customer after the first reminder. Artificial intelligence can process data on a larger scale and sees more connections. Such as the influence of changes in the supply chain on the customer’s payment behaviour. With that kind of insight, as a finance department, you know better which actions will yield the most results.
Artificial Intelligence
Artificial intelligence is also perfectly capable of performing parts of work processes independently. The system then figures out for itself how tasks lead to the best result and executes exactly that. Thus, artificial intelligence – calculated in combination with data – is also an excellent way to automate tasks. Not surprisingly, it is precisely these two technologies that are at the top of the wish lists.
Blockchain
Among financial professionals, in 2022, almost a quarter percent thought blockchain was the technology with the most impact on the order-to-cash process. That number has been stable for years. Funny really, you would expect more of it, as this technology is ideally suited for e-invoicing. Diving deeper into the figures, we see something else remarkable. In 2017, 17% of organisations were already applying blockchain, but only 9% are doing so this year. As a counter movement, the number of blockchain projects on short-term planning has actually increased sharply. In other words, blockchain seems to be on hold for a while. This is quite explainable, as it obviously involves sensitive information and, moreover, the matter is quite complex. You want to work on these kinds of projects with full attention. Due to the extra pressure that corona brought, this was not possible for a while. Once that pressure subsides, we expect finance departments to get back to business as usual with blockchain initiatives.
Robotic Process Automation (RPA)
In 2019, this was the technology that 44% of finance professionals expected the most from; in 2021, only 21% have high hopes for it. A halving, in other words. So is it that the technology is still not valuable for the order-to-cash process? On the contrary, it has actually proven to be terribly valuable and is even being widely adopted. With simple ‘if-then’ rules, numerous repetitive actions are already automated. This is already embedded in the technology even before it reaches the workplace of the financial professional. As a result, the latter is completely unaware of it. In fact, RPA is already transforming the order-to-cash process today. And it happens so naturally that finance professionals don’t notice it.
Now and soon
So we can tentatively conclude that RPA is the technology that is transforming the order-to-cash process today. In the near future, artificial intelligence and big data will be next. Of blockchain we can say less, first wait and see how those projects resume.
For more information regarding the impact of big data on the financial sector, download our whitepapers here:
- Data-driven organisations
- Customer Engagement
- A beginner’s guide to credit management software
- From risk management to bailiff
Want to have a no-obligation conversation with one of our sales specialists about the value of big data for your organisation? Contact us.
