Corona Crisis: Three Tips for an effective data-driven credit management policy


Corona Crisis: three Tips for an effective data-driven credit management policy

These are uncertain times. Lately, it’s become impossible to switch on the news without hearing about the coronavirus crisis, economic recession or the rising number of bankruptcies. However, while things are no doubt challenging at the moment, it’s likely that the biggest blow is yet to come. After all, history shows that this tends to hit when the crisis has reached its lowest point. As a credit manager, right now your biggest priority will be ensuring that your invoices are still being paid so you can maintain cash flow and ensure your organisation can continue to operate. In this blog, I’ll share my top three tips to ensure you rise to the top of your customers’ payment lists and create an effective data-driven credit management policy.

1. Adopt a personalised approach

Fast invoice payment is essential, but at the same time, you also want to maintain a good relationship with your customers. Fortunately, you can kill two birds with one stone if you know your customer well enough. To do this, it’s important to take into consideration their needs in order to improve the customer journey, while also putting the processes in place to help them in any way possible to pay their invoice on time. You can do this by personalising the tone of voice of reminders and by offering them the most relevant payment method, for example. But in order to adopt this approach, you have to firstly collect information about your customers and then work in a data-driven way.

Use both internal and external data sources and divide customers into segments based on this data. By analysing this data, you can determine which customers are high risk during economic downturns, as is currently the case, and take a different approach to those customers compared to those who are low risk. With these insights, you can take appropriate action faster if you suspect that payment problems will arise. This method can be applied both for existing customers as well as those in the prospect phase.

2. Record data and use that information

Better decisions are made using big data and artificial intelligence (AI) because they can recognise patterns that yield insights. Recording your customer’s payment behaviour provides a wealth of information and linking all this information to AI ensures that problems can be identified or even predicted at an early stage. By recognising patterns, you’ll be able to spot the first signs that a customer isn’t going to pay. You can then proactively contact the customer about paying bills to avoid arrears.

3. Become stronger together

Data-driven credit management is the responsibility of the entire organisation – especially at a time when a recession is imminent. Account managers are currently unable to visit customers and, at many organisations, the number of assignments is decreasing. It’s a shame to leave this hardworking group with little to do when they can make all the difference if they apply their talents to credit management. For example, these individuals make a significant contribution by calling customers with small payment arrears or customers who have unexpectedly not paid their invoice on time. By acting early and entering into a conversation with the customer, you can avoid bigger problems. Taking this route of communicating with customers will help you to choose the correct approach for the customer, such as showing them more leniency. With this in mind, it’s possible to create new coronavirus workflows in your credit management system, through which you can devise a tailor-made approach and offer your customers optimal flexibility.

Data-driven working will make it easier for organisations to deal with a potential recession. Of course, at this stage most businesses won’t be completely data-driven, but you can take small steps in this area by connecting your main systems and extracting insights from the data. By doing so, you’ll not only benefit from this in the short-term, but also long into the future. Start small and excel.

For more information on becoming a data-driven organisation
Read our whitepaper: The impact of data-driven organisations on daily practice

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