The role of payment profiles in collections

Apr 27, 2022

payment profiles

Estimated reading time: 7 minutes

The role of payment profiles in the collection process is rarely highlighted. Yet they can help in debtor management and ensure better results.

What is a payment profile?

A payment profile is a collection of characteristics enabling debtors to be classified into groups. The payment profile is mainly determined on the basis of (historical) payment behaviour.

Based on the payment profile, certain decisions can then be made in debtor management, such as the chosen communication channel (telephone, SMS, letter, email, WhatsApp), the tone of voice, and the language.

Why create payment profiles?

There are various reasons for creating and using payment profiles. After all, a payment profile can be used at any stage of debtor management and is a useful tool in the analysis of the debtor portfolio.

  • The payment profile can serve as a guideline for follow-up actions with certain groups.
  • A payment profile allows for more tailored communication with the debtor. The means of communication, the use of words and images, and the message are tailored to the target group.
  • The payment profile provides information for choosing a payment agreement, an instalment plan or a particular collection strategy.
  • It helps in deciding which part of the debtor’s portfolio should be transferred to the collection agency or the bailiff.

In any case, creating a payment profile is crucial in the efficient follow-up of debtors. This, in turn, should lead to better results.

How should you create payment profiles?

Debtor payment profiles should be created based on internal and external data such as:

  • The debtor’s payment behaviour. This may relate to the payment history available within your company, or the payment behaviour within a specific sector. How quickly do they pay and how quickly do they respond to payment reminders.
  • The outstanding balance of the debtor.
  • The agreed payment period, with a possible margin.
  • Credit limits and credit scores.
  • Address details or nationality.
  • Other data such as publicly available data related to the debtors’ finances.

The number of payment profiles varies greatly

The number of payment profiles varies per organisation. Often it is limited to three; but depending on the complexity of the organisation and its customers, it can easily amount to ten or more payment profiles.

The classification can be very simple: three payment profiles for good payers, less good payers and bad payers. The traffic light colours green, amber or red can be used as additional indications.

The green payment profile indicates loyal payers who almost always pay on time. Anyone in this group who, exceptionally, pays late once, will receive a simple reminder asking them to settle the payment.

The amber payment profile requires more effort as a group. You can call up these debtors, listen to what the problem is, offer a suitable solution, and so on. The challenge is to get these debtors into the green group and, especially, to prevent them from ending up in the next group, the red payment profile.

The red group consists of the most problematic payers who need a lot of time and attention and only pay after a lot of communication. You can work out a customised approach for members of this group. These are the three “basic” segments but there may well be many more.

It is important to understand that a payment profile is not static. The fact that you have assigned a debtor to a certain payment profile does not mean that this payment behaviour will be repeated in the future. People or companies can move from one payment profile to another as a result of changes in payment behaviour, changes in the company’s financial situation, etc.

Payment profiles with iController

In iController our customers set up payment profiles in different ways. We distinguish three important levels.

Manual setup

Smaller organisations often do not have the data, knowledge or time that is necessary to develop payment profiles and to deploy them in a targeted way. In such cases iController enters into a dialogue with the customer and creates segments based on the customer’s ideas.

For companies or organisations that already work with customer segments, we extract the payment history from ERP systems or accounting software. This usually concerns segments such as key accounts, segmentation into B2B and B2C, domestic and foreign debtors, export customers and intercompany segments.

For both customer groups iController helps to get insight into debtors’ payment behaviour. As an organisation you get to see whether payments have already been made, when they were made and what the average payment behaviour is. But you also find out what you had to do to get to this payment behaviour.

The underlying idea is often the same for all companies: you end up with payment profiles of bad, less good and good payers, accentuated by colour labels such as red, amber and green.

Automated phase

When customers have been working with iController for some time – but it can also be set up at the start – they often choose to drop the segmentation and let the iController platform make its own choices.

In this automated phase iController will itself assign a payment profile to debtors. For example, if the outstanding balance is higher than the sum of the internally set limit and the external limit of the business information partner, this debtor gets the red label.

You can also work with the payment behaviour and give the debtor a red score when the payment behaviour (the number of days paid after the due date) is greater than the sum of the agreed payment period and a fixed percentage (e.g. 20%).

Manual interactions are still possible. If, for example, information from an external business information partner shows that the customer always pays too late, but your own data shows that this always happens two weeks after the due date, you can deliberately choose to move this to the green group, because the payment behaviour remains stable, and you therefore do not have any extra work as a credit controller.

Predictive phase

The algorithms on which payment profiles are based perform better when more data is available: more outstanding invoices, more debtors, and more data on payment behaviour over a longer period.

In a third phase that will be fully rolled out this year, we’ll therefore be making use of our Advisory AI application. It puts big data from your iController platform to work, optimising your company’s cash flow.

Specifically, the advanced AI technology:

  • Predicts when the debtor will pay an invoice
  • Gives credit controllers insight into possible actions
  • Provides advanced simulations of payment behaviour
  • Determines the optimal procedures in credit management
  • Maximises the efficiency of credit controllers by optimising the workflow

Treat it as your personal assistant who gives you recommendations and proactively tells you, “If you carefully follow these procedural steps, you will see these improvements in the number of outstanding invoices.”

Ask yourself the following questions:

  1. What did I have to do to arrive at the payment behaviour we see today?
  2. What can I do to improve payment behaviour?
  3. How can I use the insights that iController gives me to organise my work better?

The added value of payment profiles

Whatever the complexity or degree of automation in accounts receivable management, working with payment profiles offers many advantages.

Better service to debtors

Payment profiles provide a more targeted and better service to the customer or debtor. The communication for certain target groups is customised, deploying a predetermined communication channel, a specific tone of voice, and specific word and image usage.

The right approach can also limit extra costs or extra procedures for the debtor. After all, it is possible to get on the ball more quickly: payment problems can be detected at an early stage, specific payment arrangements can be proposed, and legal proceedings or increased interest and costs are less likely to occur.

Better collection results

In practice, the use of payment profiles leads to better collection results. However, the initial set-up and elaboration of these payment profiles has to be taken into account.

Credit management software such as iController helps companies to assign debtors to specific procedures and to set up efficient workflows for credit controllers.

An efficient process

With payment profiles, you ensure that the collection process is structured, reducing the demands placed on resources and people. It also prevents problems from escalating and debts from mounting further.

The payment profile can also be used by a collection agency to determine the rates for its customers.


Payment profiles are supportive in the workflow and when communicating with customers. They help you to make decisions about how to follow up on a customer. With iController, all options are open when working with payment profiles.

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