Saeij Onguard marieke

Almost two-thirds (64%) of UK CFOs expect to be completely reliant on big data within five years, according to research conducted by Onguard.

Its research found that 13% of CFOs say they are already completely reliant on insights provided by big data, with most using it to support decisions (54%), make predictive analyses (41%) and to analyse large, unstructured databases (29%).

According to the 2019 Fintech Barometer, an annual survey conducted by the order-to-cash specialist, more than one-third of CFOs (38%) expect big data to have a significant impact within the financial sector, particularly on aspects such as job opportunities, while 36% see it as a threat to employment.

Marieke Saeij (pictured), chief executive of Onguard, said: “Big data can help CFOs, as well as finance professionals within their organisations, with the execution of their work.

“Finance professionals have a great deal of information from both internal and external sources that is of added value for both the performance of the organisation and customer service. The more information that is available about the market and customers, the better finance professionals can advise customers.”

She added that big data allows risks to be assessed more accurately and it is also possible to predict in real-time any potential issues with payment.

Saeij said: “This development will require finance professionals to develop new skills, such as greater analytical capacity, as a necessity.”

Recently, Onguard announced a collaboration on a new service to be launched next year that will use machine learning to predict customer payment behaviour.

The new platform will combine historical data from Onguard’s software, external debtor information from business data expert Altares Dun & Bradstreet and a machine-learning based scorecard from Quantforce, based on invoice and payment history.

Debtors can be ranked in order of the risk of non-payment, which enables finance companies to introduce planning at an early stage using automated workflows.

When it is predicted that a customer will not pay or pay too late, it is possible to respond immediately.