Digital transformation in credit management: how far have we come?

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In a previous blog just over three years ago, we discussed then-nascent technology – including artificial intelligence (AI) and Robotic Process Automation (RPA) – and its potential to shake up the credit management process for suppliers. So how far have we come and what obstacles remain for digital transformation?

Big data and AI

These two developments were widely expected to have the greatest impact on the order-to-cash process and professionals still cite them as having the most potential going forward.

Together, big data and AI can be particularly powerful credit management tools. Where previously data was treated in siloes, AI now allows vast swathes of data to be sifted and prioritised. This ensures greater visibility and providing a robust foundation for making both strategic and everyday decisions.

Today, organisations must collect and assimilate data on a large scale. There comes a point where the human brain can no longer make the necessary connections or, at least, it requires more time and resources to do so. AI detects these connections – changes in a customer’s supply chain that may affect payment behaviour; payment habits that organisations with similar structures exhibit; measures that have helped comparable firms pay their invoices –filtering, structuring, and assessing all relevant data in real time. With insights such as these financial departments can gain a clearer understanding of each individual client, and therefore which course of action is likely to yield results.

Despite these technological advances, CFOs and credit professionals still report issues with the way organisations manage data. Instead of having one source of the truth, data is often duplicated and stored in various locations. Complex structures and multiple owners create real problems and while many recognise the routes to resolving them – investment in new technologies, automation of key tasks, upskilling of staff, and greater cross-departmental collaboration – there is often little budget to do so.

Robotisation (RPA)

Robotisation (also known as robotic process automation or RPA) is more straightforward than its AI peers. Programming hard ‘if-then’ rules can automate repetitive actions in your work process. Being reading, filtering and showing data in place Y when condition X is met. While this might appear to have limited use in comparison, robotisation can add great value in the order-to-cash process.

The order-to-cash process is data heavy and repetitive, so RPA’s ability to alleviate pressure on professionals is a significant benefit. In 2018, finance professionals in the Netherlands were already recognising its potential. For the UK however, it was not yet on most firm’s radars. Since then, however, we have seen expectations for RPA’s value in the credit management space sink lower for both markets. At Visma | Onguard, we think these figures distort the real picture. Research from Deloitte in 2019 showed that a quarter of the world’s leading companies were already deploying RPA on a large scale, and 80% of them were looking to expand the scale rapidly.

RPA in practice

According to the latest findings from our annual Fintech Barometer survey, 25% of Dutch companies were investigating RPA in 2021 and 40% of British firms had already made plans to implement it. There are certainly projects in the making but as finance professionals grow more digitally savvy the integration of RPA into their everyday processes can easily be overlooked. It is likely that many are unaware that their organisations are already adopting RPA. It is often encoded in the software they use, in workflows, or in debiting payments, for example. This is also true for AI, says respondent Michel van Leeuwen, Director of Corporate Communications at Flanderijn:

“It is quite possible that finance professionals are not aware of the fact that they already apply RPA and artificial intelligence through the software they use. At Flanderijn, we apply RPA more and more because we find it an excellent way to automate simple actions.”

What are the barriers?

A lot has changed since we began our research in 2018. COVID-19 and market uncertainty have brought huge changes to customer payment behaviour, while many organisations have simply been unable to pay their invoices on time. Financial processes are in a state of flux and finance departments have no choice but to respond. This has led to mounting pressure both at a strategic and day-to-day level. In both the UK and the Netherlands, financial professionals are looking to technology for the solution.

Fintech solutions that can leverage big data, in combination with innovative developments in AI and RPA, can automate repetitive tasks and support processes in many areas. Implemented correctly, this frees up the financial department to add value where it is most needed. Including to help further develop relationships with the customer base. This in turn leads to a lower day sales outstanding (DSO) and an increase in working capital available for investments.

What the future brings

Digital transformation remains high on the agenda for most firms, as does the push towards real-time reporting. Our data suggests that the Netherlands is two to three years ahead of the UK in its digital transformation journey. Despite the difference in pace, the underlying organisational challenges preventing successful digital transformation are similar. The biggest are lack of time and prioritisation within the company.

Professionals see plenty of potential to take the entire financial process to the next level, but we are not there yet. To move forward requires an internal dialogue about the true value that technology can bring.

 

Visma | Onguard’s Fintech Barometer is an extensive annual survey of financial professionals. This research, which we have conducted in the Netherlands and the UK for four consecutive years, gives us a unique insight into the application of fintech solutions, and the pace at which organisations are managing to embrace it.

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