Big data in finance: from descriptive to prescriptive analytics


Big data in finance: from descriptive to prescriptive analytics

Companies and consumers are both preoccupied with data. Companies want to know how they can make the best use of the data they gather, while customers try to ensure that companies collect as little data about them as possible. Data is hot and, in our technology-driven world, everyone is engaging with it in one way or another. Business customers and consumers are often reluctant to provide data, yet it is in their interest to do so. So it is also important that companies use data to continually enhance the customer experience. At the Onguard Academy, organised by FinTech company Onguard and commercial data supplier Altares Dun & Bradstreet, finance professionals learned more about the possibilities of big data in finance.

Old approach in a new guise

“What we see happening today is not as new as you might think!” The Onguard Academy opened with these words from Joris Peters, a Data Scientist at Altares Dun & Bradstreet. He was referring to credit (risk) management. The importance of credit risk management (also known as receivables management) was recognised back in Ancient Greece. Some 2,300 years ago, the Greek philosopher Aristotle is reported to have said: “Creditors have no specific interest in their debtors, but only desire that they may be preserved, such that they may repay.” In other words, Aristotle recommended that creditors treat their debtors well because it increased the likelihood of payment.

This is still the essence of 21st-century credit management. However, the way companies organise credit management has changed and this has to do with the times in which we live. New technology and computing power are the main changes. Today, computers and other devices are capable of highly efficient and more sophisticated data capture. They also have far greater storage capacity. They capture and transmit millions of data units daily. Data is everywhere. It can be easily stored and fed into machine-learning algorithms. Ignoring data is no longer an option. And this also applies to the world of credit management. We now have so much information about the individual debtor. It’s time we used this knowledge to improve their customer experience.

From descriptive to prescriptive analytics

Though it may have gone unnoticed, we have actually been working with data for many years. The use of data is not new. But, by combining large sets of (un)structured data from different sources, it is now possible to use data not only as a basis for informed decisions but also to predict customer and debtor behaviour. This is what we mean when we talk about ‘big data’. The use of big data involves three dimensions of analytics competency. Ultimately, we want to progress to the third dimension. This enables companies to make a real difference. The three dimensions of data analytics competency are:

  1. Descriptive: The volume of available data allows finance professionals to look at the facts, past and present. At this level, the use of big data is pretty straightforward.
  2. Predictive: It is possible to run analytics on historical (descriptive) data and identify payment patterns. These patterns can be used to predict what might happen tomorrow. At this point, we are approaching the final dimension.
  3. Prescriptive: The third and most interesting dimension of big data analytics is the prescriptive level. Once you can predict that a debtor will pay late or default, it is wise to take action. You can then preempt potential problems before they occur. Herein lies the promise of the prescriptive dimension of big data analytics.

What does this mean for the credit manager?

Big data can make a difference, in organisations in general and in finance departments in particular. The majority (88%) of finance professionals anticipate that two years from now, their departments will not be able to operate without big data. This was one of the findings of the annual Onguard FinTech Barometer survey. But what does it mean for the credit manager? The use of big data is causing credit managers to wonder about their future in the industry. The FinTech Barometer survey also revealed that 42% of them believe big data will have a significant impact on employment. This is both logical and inevitable. Jobs are always evolving and big data is a game changer in this respect. By enabling companies to anticipate certain risks well in advance, it can be used to preempt potential problems with customer payments, thereby reducing Days Sales Outstanding and increasing cash flow.

Big data also gives companies a complete overview of their business processes and their status, so the senior management and the board can make informed decisions about the future of the company. So, will the use of big data erode the role of the credit manager? Well, that depends on how they approach it. Credit managers are facing a new challenge: they have to assume a more strategic role and they also have to be able to analyse the data so they are a valuable addition to the management. This is how your company can make a difference.

For further insights into the impact of big data on the finance industry
Read our whitepaper "Big Data"

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