Predicting Customer Payments in the Automotive Industry with Microsoft Dynamics 365 Finance

In the automotive industry, maintaining a healthy cash flow is critical to sustaining operations and fostering growth. Predicting customer payment behaviors can significantly impact financial planning and decision-making. Microsoft Dynamics 365 Finance offers a robust Customer Payment Predictions feature that leverages AI to forecast payment trends and enhance financial efficiency. This blog explores the importance of customer payment predictions for automotive businesses and provides a guide on how to use this feature effectively.

The Importance of Customer Payment Predictions for the Automotive Industry

Automotive companies deal with a complex supply chain and significant financial transactions, making it essential to predict customer payments accurately. Here are key benefits of utilizing customer payment predictions in Microsoft Dynamics 365 Finance:

1. Improved Cash Flow Management

• Timely Payments: Predicting when customers are likely to pay helps manage cash flow more effectively. Knowing which invoices are at risk of late payment enables proactive measures to ensure timely collections.
• Optimized Working Capital: Accurate payment predictions help optimize working capital by reducing the uncertainty of incoming cash flows. This ensures that funds are available for critical operations and investments.

2. Enhanced Credit Control

• Risk Mitigation: By identifying customers who are likely to pay late or very late, businesses can mitigate risks by adjusting credit terms or taking preemptive actions to secure payments.
• Informed Decision-Making: Payment predictions provide valuable insights for making informed credit control decisions, such as extending credit to reliable customers or taking legal action against habitual late payers. For more information on issuing promissory notes in the automotive industry, check out our recent blog post here.

3. Strategic Financial Planning

• Budget Accuracy: Accurate predictions of customer payments improve the accuracy of budget forecasts, enabling better financial planning and resource allocation.
• Long-Term Planning: Understanding payment trends aids in long-term financial planning, helping automotive businesses prepare for future market conditions and financial needs.

Using Customer Payment Predictions in Dynamics 365 Finance

Once the Customer Payment Predictions feature is configured, automotive businesses can leverage it to enhance their financial operations. Here’s how to effectively use the feature:

1. Accessing Payment Predictions

Navigate to the Manage customer credit and collections workspace in Dynamics 365 Finance. Here, you will find two new tiles: Transaction Payment Predictions and Customer Payment Predictions.

2. Analyzing Transaction Payment Predictions

On the Transaction Payment Predictions list page, view the probability of payment for open transactions in three categories: On time, Late, and Very late.

• On-Time Probability: This column shows the likelihood that an invoice will be paid on or before the due date. If the probability is below 50%, a red indicator appears, highlighting the risk of late payment.
• Payment Details: Select a transaction to view detailed predictions, including the factors influencing the payment probability. The Top Factors section reveals attributes impacting the prediction, such as customer payment history and transaction specifics.

3. Reviewing Customer Payment Predictions

On the Customer Payment Predictions list page, see the total open balance and the predicted amounts in the On time, Late, and Very late buckets.

• Payment Buckets: The amounts in each bucket are calculated based on the weighted average of the transaction balances and their respective payment probabilities. This provides a comprehensive view of expected cash inflows.
• Customer Insights: The Customer Insights FastTab shows current invoice, payment, and collections statistics, while the Customer History FastTab displays historical payment trends. These insights help validate the prediction model’s efficacy.

4. Improving Model Accuracy

If you are not satisfied with the accuracy of the predictions, you can improve the model by selecting the Improve model accuracy link in the Finance insights parameters.

• Customizing Fields: Use the AI Builder extension to select or deselect fields that influence the prediction model. Tailoring the model to include the most relevant data enhances prediction accuracy.
• Retraining the Model: After adjusting the fields, retrain the model to apply the changes. The updated model will be used for future predictions, ensuring continuous improvement in forecasting accuracy.

Setting Up Customer Payment Predictions

Correct set up within Microsoft Dynamics 365 Finance is essential to ensure accurate predictions. Follow these steps:

1. Navigate to Configuration: Go to Credit and collections > Setup > Finance insights > Customer payment predictions.
2. Enable the Feature: On the Customer payment predictions tab, enable the feature and specify the “very late” transaction period.
3. Create the Prediction Model: Define the prediction model using at least 100 settled transactions across On time, Late, and Very late categories. The system will then create and train the model based on this data.

Conclusion

Customer Payment Predictions in Microsoft Dynamics 365 Finance is a powerful tool for the automotive industry, providing critical insights into customer payment behaviors. By leveraging AI-driven predictions, automotive businesses can improve cash flow management, enhance credit control, and make more strategic financial decisions. Implementing this feature enables businesses to navigate financial complexities with greater confidence and precision, ensuring sustained growth and operational efficiency.