Remittance matching: How can AI solve these issues?

Featuring receivables experts Mark Brousseau of Brousseau & Associates and Beth Bourgoin of Deluxe, IOFM’s recent webinar, “Top 3 Strategies for Fully Automating AR Processes,” helped organizations learn how to approach integrating digital solutions into their existing AR processes. Sponsored by Deluxe, the webinar took a deep dive into the latest IOFM research on the challenges of digital implementation and automation, as well as key strategies to maximize your digital payments.

During the Q&A portion of the webinar, an attendee asked for more clarification on how automation can help solve common AR challenges: “How much of the remittance matching issue can really be fixed using artificial intelligence and other automated tools?”

Deluxe’s Integrated Receivables Product Manager Beth Bourgoin says, “I’m smiling at that one. The reason I love and appreciate that question is, it's not going to solve for a hundred percent. Whenever talking to corporates, I like to level set and say, ‘Don't expect perfection here. It really is as good and is going to work as good as the data you receive.’”

Bourgoin explains there are predictable scenarios from an organization’s customers that can be solved with the use of AI. For example, if you’re only receiving a partial invoice number, the AI will be able to easily match the remittance data.

“The AI has specific use cases it'll solve for. It'll help with automating research. And what it does is take the data from the payment, the data from the remittance details, and then also look at data from your ERP system. And that's why it's able to be so successful,” Bourgoin continues. “We have seen straight-through processing rates in the mid 90%, especially higher when it comes to electronic payments. There actually was a customer where 98% of their data goes through automatically.”

Bourgoin notes that not everyone is going to get to 98% straight-through processing rates, because it depends on numerous factors: what you receive from your customers, what your AP systems look like, etc. The recipe for success in remittance matching is really having access to some data points from your ERP system. The AI can then have three separate points of data (the payment, the remittance and the ERP) to go in and match everything against.

“It really is quite impressive,” adds Bourgoin, who referenced a corporate client whose tasks would take eight to 12 hours to do, can now complete their remittance matching in about 15 minutes. While there’s still work to be done, the process may be reduced further to even two minutes, automation and AI tools lead to increased time and cost savings.

“It’s not going to solve for everything you get. But that’s where the research and the scenarios that you see from your customers is really going to help you understand how successful you’re likely going to be. Do you offer discounts, taxes, net discounts if you pay within certain net terms? All of that is really going to impact how successful the AI is,” Bourgoin explains. “There are more conversations to have there that are specific to your corporation – but also a lot of potential for success.”