Becoming data-driven successfully in credit management

Martijn Juliana data-driven finance

Credit management has undergone a significant transformation in recent years. Whereas credit management was previously seen as the back office’s grab-can, today it is an essential part of an organisation’s financial strategy. In the process, the challenges posed by COVID-19, persistent inflation and rising interest rates also require a different, more proactive and sophisticated approach. With this approach, data-driven working is also becoming increasingly important. But data-driven working within credit management is not easy to achieve. Companies that are working data-driven successfully have made a number of changes in recent years.

1. From Excel to ERP systems

Working in a data-driven way starts with collecting the right data. Think of data such as company size, sector, locations, payment history and creditworthiness. To collect this data, you can consult both internal sources and external sources, such as Altares Dun & Bradstreet. Besides the fact that the data must be correct, it is of course also important for accurate analysis that this data is of high quality.

In the past, when creating reports, many finance teams struggled to gather credit management data from various spreadsheets. They were sometimes spending several working days a month gathering the right data and analysing it before they could act on their findings. In many cases, the data was actually outdated by then.

Today, organisations are much better at collecting data on their credit management. Whereas in 2020 Excel was still number one, today 41% of finance professionals work with an ERP system. This allows finance professionals to always have access to the data they need, making organisations increasingly capable of making data-driven decisions.

2. Data-driven through advanced data analysis skills

After collecting the right data, one needs to analyse it properly to generate valuable insights. New tools, techniques and best practices to do this are constantly entering the market. For instance, AI and machine learning are playing an increasingly important role in this. It is therefore wise to have your feelers turned on for this. In doing so, it is valuable to develop the right skills to do (new) data analysis. For instance, you may need knowledge of modelling to better predict risks and opportunities.

3. From traditional working to an innovative culture

Finally, implementing data-driven working within credit management is not only about learning new technical skills, but a cultural shift must also take place. Namely, a culture needs to emerge in which employees see the added value of data-driven decisions and dare to trust these choices. To achieve this, you need to actively include employees in the changes and inform them about what data-driven working will bring to them. That way, they will be more likely to be open to new ideas and insights based on data.

Becoming data-driven, step by step

If, as an organisation, you want to operate fully data-driven within credit management, these are the most important changes to work on. It may seem daunting, but don’t be discouraged. Start with small steps and prepare your data-driven capacity little by little. Then you’ll make working in a data-driven way within credit management a success.



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