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A company’s payment behaviour is a good indicator of its financial situation. If you have insight into your customers’ buying behaviour, you have more control over figures such as DSO (Days Sales Outstanding) and you can take appropriate measures.
And although insights into payment behaviour are typically based on historical data – which provides no guarantees for what will happen in the future – a number of things can be inferred from them.
In this blog we explain what payment behaviour is and we go deeper into the ways you can discover (changing) payment behavior.
What is payment behaviour?
Payment behaviour considers the speed at which customers pay invoices, and how this compares to the agreed term. If a debtor pays the invoice on average seven days after the due date, we refer to this as a payment behaviour of +7 days.
In an ideal world, invoices would always be paid correctly according to the agreements made and within the payment term. Unfortunately, this is not the case for every debtor and in practice many invoices exceed the payment term. The question therefore arises as to how much this costs.
Change in payment behaviour
Payment behaviour says a lot about a debtor, but a change in payment behaviour is also an important determinant. If the same debtor in the above example always pays the invoices seven days after the due date, there is no change in the payment behaviour, so the figure is 0. Although the debtor always pays late, the behaviour is consistent, and is therefore largely predictable.
However, a debtor who is always paying invoices at different times exhibits a variable payment behaviour. That fluctuating figure may be an indicator of increased risk with regard to this debtor. Perhaps the customer has a reduced cash flow? Or perhaps things aren’t running all that smoothly within the company?
Good credit managers and credit controllers continuously monitor payment behaviour and changes in the payment behaviour of each debtor. Prospects are also best subjected to a thorough analysis in advance. Even more so when large sums are at stake.
How do you get insight into payment behaviour?
One way or another, you need to analyse the payment behaviour of potential and existing customers. You can examine your own invoices and internal data to shed light on this, but external tools are also available.
Agreed payment term
The first indicator is the agreed payment term. When it has been agreed that a customer will pay within thirty days, the customer must also keep to that agreement. Ask yourself what degree of late payment, or overrun on the payment term, you regard as acceptable, and what you find unacceptable.
The overrun may depend on the sector or it may be specific to the debtor. For some sectors, specific payment terms may apply, which you can take into account.
According to the Exact SME monitor 2020, which is based on the management of 340,000 Dutch companies, the average payment terms per sector are as follows:
- Construction: 26.91 days
- Commerce: 31.43 days
- Accountants: 32.96 days
- Manufacturing: 34.65 days
You can find out the payment behaviour of your own debtors in various ways; ageing analysis is one of them.
Unpaid invoices go through several stages. Ageing analysis indicates the stage of the process that the unpaid invoices are in. These stages are usually classified based on the length of time that the invoices have already been outstanding. For example, 0 days for non-overdue invoices, while overdue invoices are classified as 1 to 30 days, 31 to 60 days, 61 to 90 days, and so on.
With this information you can make a better judgement of what follow-up actions are needed. For very bad payers you can, for example, adjust future payment terms or start asking for an advance.
Payment behaviour per invoice
The next indicator is payment behaviour per invoice. In this way you can detect whether the debtor pays invoices with smaller amounts than those with high amounts.
Changes in total amount per year
When the total amount per year decreases with a customer, you have to be extra vigilant as a debtor manager.
Changes in payment time intervals
If the debtor makes payments later and later or the times of payment start to fluctuate, this can be a harbinger of payment problems.
If you would like even more insight into payment behaviour, also of new customers, you can contact specialist trade information agencies such as Dun & Bradstreet or Graydon to request a report on the creditworthiness of companies.
Such agencies calculate creditworthiness based on many variables and factors. These include historical payment behaviour, turnover, and outstanding obligations. Depending on the provider, creditworthiness is expressed in figures or a rating.
If you combine your own internal data with the data from these external parties, you will gain even better insight into the creditworthiness of customers, and you can predict payment behaviour even more accurately.
With iController, this credit score is baked into the solution. In addition to the credit score of these external parties, our own personalised iController score will also take into account the payment behaviour of a customer towards your company.
After all, companies with low creditworthiness aren’t necessarily bad payers. Conversely, companies with high creditworthiness are not necessarily good payers to your company.
You can link the iController score obtained in our debtor management software to a specific follow-up process.
Predicting payment behaviour with AI
To make even better decisions, you need more data. iController’s advanced AI technology provides thorough, accurate cash flow forecasting and can accurately predict when a customer will pay, using statistical analyses.
Suppose a customer usually pays after 30 days, but once paid after 60 days. A statistical analysis then calculates the average: the customer pays on day 45. iController’s AI tool recognises the late payment as an exception and expects the next payment to be made after 30 days, unless further late payments follow.