Payer rating

The payer rating predicts payment behaviour and is generated using a machine learning model.

Payer ratings are available for all of your customers who have at least one paid invoice. These are visible in Chaser on the customer tab in receivables and also on the customer page (see images below).  

Each of your customers in Chaser will be assigned a rating. This rating predicts how likely they are to pay their future invoices on time. 

How can I use the payer rating to improve my credit control processes?

The payer rating can help you

  • Compare your customers (who are the best and worst payers)
    • See who your worst debtors are and focus on them
  • Group customers based on ratings 
    • You may choose to create different schedules using your customers payer rating so that you can adapt the frequency and the way that you chase them.
  • Understand your risk (how many bad payers you have / how many invoices are at risk of being paid late)
    • Produce periodical reports based on customer ratings to give insights on good/bad payers percentages on the total amount of receivables
  • Adapting credit limits (e.g. when your customers become bad payers, you may consider reducing their credit limit so that you decrease the risk to your business)

What data is required in order for my customer to receive a score?

In order to be assigned a rating, the customer must have at least 1 paid invoice.

How are payer ratings calculated?

The payer rating takes into consideration the customer's previous payment behaviour. Using this, it will make a prediction of how likely the customer is to make payments on time. The customer is given a score, which is transferred into a generalised rating: Good, Average or Bad. 

The calculation takes into consideration the following:

  • Day of Week of Due Date
  • Week of Year of Due Date
  • Year of Due Date
  • Total Difference in days between Due Date and Paid Date (Days Delay)
  • Days Delay for Previous Invoice
  • Days Delay Moving Average (windows of 2) for Previous Invoices
  • Std. Deviation of Days Delay for the Previous Two Invoices
  • Total Value of the Invoice
  • Total Value of the Previous Invoice
  • Total Value Moving Average (windows of 2) for Previous Invoices
  • Std. Deviation of Total for the Previous Two Invoices
  • Invoice is Paid Late (1 if True, 0 if False)
  • Previous Invoice is Paid Late (1 if True, 0 if False)
  • Total Number of (Previous) Invoices Paid Late