Use Customer payment predictions

This topic explains how to use the Customer payment predictions. Before you use this feature, make sure that you've completed the setup steps for it. For more information, see Enable customer payment predictions.

You can view customer payment predictions in the Manage customer credit and collections workspace and on two new list pages, Payment predictions per transaction and Payment prediction per customer.

Manage customer credit and collections workspace

The Manage customer credit and collections workspace includes two new tiles, Payment prediction per transaction and Customers with predicted high late balances.

  • The Payment prediction per transaction tile shows the number of open customer transactions that have a probability of payment that is less than 50 percent in the On time bucket. You can select this tile to open the Payment predictions per transaction list page.
  • The Customers with predicted high late balances tile shows the number of customers for which more than half (50 percent) of the total balance is predicted to be paid late and/or very late. You can select this tile to open the Payment prediction per customer list page.

Manage customer credit and collections workspace.

Payment predictions per transaction list page

On the Payment predictions per transaction list page, you can view the probability of payment for open transactions in the On time, Late, and Very late buckets. For each transaction in the grid, the On time probability column shows the probability that the invoice will be paid on or before the due date. If the probability of an on-time payment is less than 50 percent, a red circle appears next to the percentage in the On time probability column to indicate the risk of late payment.

Payment prediction per transaction page.

The Related information pane on the right side of the page shows more details about the predictions:

  • For the transaction that is selected in the grid, the Payment prediction FastTab shows the details of the payment predictions in the On time, Late, and Very late buckets. The Top factors section shows the top factors that influenced the predictions. The top factors are attributes of the selected transaction and/or the customer for that transaction.
  • The Customer insights FastTab shows the current invoice, payment, and collections statistics for the customer for the selected transaction.
  • The Customer history FastTab shows the customer's payment history in the On time, Late, and Very late buckets.

The data in the Top factors section, and on the Customer insights and Customer history FastTabs, helps explain the payment predictions. It can help increase your confidence in the efficacy of the predictions.

Graphical indicators for payment predictions in the Related information pane.

Payment prediction per customer list page

The Payment prediction per customer list page shows the total open balance, and the amount that is predicted to be paid in the On time, Late and Very late buckets.

Payment predictions per customer page.

The payment amount in each bucket is calculated as the sum of the weighted average of the transaction balance. This amount is calculated based on the payment probabilities in each bucket.

For example, a customer has three open transactions that have the following payment probabilities in each bucket.

Transaction Amount On-time payment probability Late payment probability Very late payment probability
T1 100 10 percent 50 percent 40 percent
T2 1,000 50 percent 30 percent 20 percent
T3 10,000 1 percent 4 percent 95 percent

In this case, payments are projected for each bucket in the following way.

Buckets Transaction T1 Transaction T2 Transaction T3 Total
On time 100 × 10 ÷ 100 = 10 1,000 × 50 ÷ 100 = 500 10,000 × 1 ÷ 100 = 100 610
Late 100 × 50 ÷ 100 = 50 1,000 × 30 ÷ 100 = 300 10,000 × 4 ÷ 100 = 400 750
Very late 100 × 40 ÷ 100 = 40 1,000 × 20 ÷ 100 = 200 10,000 × 95 ÷ 100 = 9,500 9,740

The Related information section on the right side of the page shows more details about the predictions:

  • For the transaction that is selected in the grid, the Payment predictions FastTab shows the details of the payment predictions in the On time, Late, and Very Late buckets. The Top factors section shows the top factors that influenced the payments. The top factors are attributes of the selected transaction and/or the customer for that transaction.
  • The Customer insights FastTab shows the current invoice, payment, and collections statistics for the customer for the selected transaction.
  • The Customer history FastTab shows the customer's payment history in the On time, Late, and Very late buckets.

The data in the Top factors section, and on the Customer insights and Customer history FastTabs, helps explain the payment predictions. It can help increase your confidence in the efficacy of the predictions.

Improving the accuracy of payment predictions

You can view the accuracy of payment predictions by going to Credit and collections > Setup > Finance insights > Finance insights parameters. On the Customer payment insights tab, the Prediction model section shows the accuracy of the prediction model as a percentage.

Accuracy of payment predictions.

If you aren't satisfied with the accuracy, select the Improve model accuracy link to open the AI Builder extension experience. In the AI Builder extension experience, you can select or cancel the selection of fields until you've selected the fields that you believe are most important for accurately predicting payment probabilities. When you've finished, you can easily retrain the prediction model and publish your changes. The newly trained prediction model will automatically be picked up for predictions in Dynamics 365 Finance.

AI Builder extension experience.

Release details

Finance insights public preview is available to try for deployments in the United States of America, Europe, and the United Kingdom. Microsoft is incrementally adding support for more regions.

Public preview features can and should be turned on only in Tier-2 sandbox environments. Setup and AI models that are created in a sandbox environment can't be migrated to a production environment. For more information, see Supplemental Terms of Use for Microsoft Dynamics 365 Previews.