Use cases of AI in the order to cash (O2C) process

Order-to-cash (O2C) is a vital process in any business – bridging the gap between delivering a product or service to your customers and receiving the much-anticipated payment. We can view O2C through the lens of accounts receivable (AR). This mechanism enables your AR team to bring cash into the business effectively.

As your business grows, so does the complexity and demands of the O2C process. It can become increasingly exhausting for your AR team to manually manage the growing volume of transactions.

That’s where accounts receivable automation  comes in. However, technology is continually evolving, and Artificial intelligence (AI) is poised to improve AR automation further.

AI already handles parts of the order-to-cash cycle, from customer data entry to predicting which invoices will be paid late. We’ll look at how AR automation has transformed O2C and how AI can take it further in the foreseeable future.

Here’s how to integrate AI in automating your O2C cycle

Customer data entry

AI can automate entering data of customers. This cuts the time your team spends keying information into systems.

Examples include customer data, order details, and payment information. This automation significantly reduces the occurrence of errors and enhances overall efficiency. For instance, AI can be used to extract relevant data from scanned documents or automatically complete credit application forms, eliminating the need for manually entering data.

Credit risk management

Integrating business credit scores into your credit application and accounts receivable process can help you determine the credit risks of potential and existing customers. Soon, AI can also be used to analyse large amounts of data, such as customer financial information, to identify patterns that may indicate a risk of default. The information provided by AI can complement business credit reports in helping you determine the credit risks of potential customers.

Another area where AI can be helpful is in setting and extending credit terms to your customers. AI can be used to personalise credit term decisions for each customer. AI can use data from the business credit score, income, and debt-to-income ratio to determine the ideal credit terms. This can help decrease payment defaults and increase customer satisfaction.

Invoice processing

AI can automate invoice processing. This includes verifying the accuracy of the information, matching invoices to purchase orders, and reconciling payments to invoices.

Starting small with accounting software or ERP can help with invoice processing for growing businesses. However, AI can be useful for businesses handling millions of invoices. For example, AI can identify patterns in millions of invoice data and flag potential errors. Instead of having your staff remedy errors that an accounting software has missed, you can instruct AI to detect and resolve errors, using the same business rules your staff would apply in such situations.

This can help to improve efficiency and accuracy. Your AR team would then have more time to do work that grows your business.

Order fulfilment

AI can provide real-time visibility into the progress of orders from the time a customer places an order. AI can also improve inventory management by helping ensure products are always in stock and that orders are shipped quickly and accurately.

Big retailers, such as Walmart, use AI to reduce errors and increase efficiency in their supply chain. This helps to speed up order fulfilment times.

Writing invoice reminders

By providing prompts, you can instruct AI to generate appropriate content and adopt the desired tone of voice to use in your invoice reminders. The AI system can analyse data from previous effective reminders that have elicited responses or prompted successful payments. Machine Learning (ML) helps improve the quality and effectiveness of AI in writing invoice reminders. This data-driven approach increases the chances of a successful outcome.

Payment reminder templates for email and SMS

Payment transactions

AR automation software has already established the foundation for automating payment collections. This includes tracking payments, monitoring due dates, sending reminders, and following up on late payments.

In the near future, AI has the potential to transform payments in AR automation. It can identify patterns in payment data such as the channels and payment methods used by customers.

AI can also help predict when payments are likely to be late. This is an exciting development that could have a major impact. Businesses can then use the collected information to prioritise collections efforts and develop targeted payment collection strategies.

The future of AR automation with AI

As automating transactions becomes more sophisticated, we expect more AI to be used in AR automation to improve the O2C process. AI can help businesses in various ways. It can automate tasks, improve visibility, make predictions, and detect fraud. This can lead to increased efficiency, reduced risk, and improved profitability.

Interested to see how you can use AI in your accounts receivable process now? Speak with one of our AR experts to learn about options for your business.