How AI will improve invoicing processes and free up time
Artificial intelligence (AI) is taking up residence in every facet of business, with new applications launching every day. Chatbots take tedious work formerly done by humans and speed up the process with virtually zero intervention.
Machine learning allows computers to save massive amounts of time for doctors by taking over the interpretation of MRI results. And of course, one of Google’s AI contributions is a privacy app that will tell you when someone is peeping over your shoulder at your monitor.
We’re in luck: AI has practical applications in the world of invoicing as well. Applying AI to invoicing has the potential to save time, money, and lots of headaches. Here are just a few of the ways we expect AI to shake up invoicing in the near term:
Detecting invoice fraud before it happens
Invoice fraud is rampant these days. Take a look at the headlines any day of the week, and you’ll see news about businesses and individuals getting swindled. And to make matters worse, accounts payable (A/P) departments are generally inundated with backlogged invoices. There are plenty of tips and tricks on how to detect invoice fraud, but many would-be readers are too buried in invoices to be proactive.
AI is poised to help reduce the very expensive problem of invoice fraud. Instead of looking for instances of fraud in each invoice, one-by-one, A/P staff will be able to teach computers what types of inputs to verify and which indicators spell fraud.
AI can verify customer information, invoice data, and banking details before making a payment. The process can include looking at both valid and fraudulent historical invoices, to understand what to pay (and what to flag for review). And over time, AI-enhanced invoicing can learn from incoming data to surface potentially fraudulent invoices - before they get paid.
Tweaking invoicing processes for optimal cash flow
If you’ve got a close eye on accounts receivable, you might have an idea of who pays early or on-time, and who’s always late. Unfortunately, just knowing who’s on-time and who’s not doesn’t give you any actionable insights. AI may be just the tool you need to fill that gap.
Imagine a computer going through all your accounts receivable records. Not only does it have historical data on timeliness of payments, it also knows the longevity of the customer, the payment method used and the amount paid each time, where they are located, whether it is a business or a consumer, and so on.
You can use AI to crunch your accounts receivable (A/R) data, find some insights, and turn them into actions that will improve invoicing outcomes. Are customers who receive expiring coupons more likely to pay on-time? Are other customers who use specific payment methods more likely to make late payments? If so, you can introduce new test scenarios and watch to see if they speed up outcomes.
Maybe adding those time-based discounts to the majority of customer accounts gets you from 60 to 90 percent on-time payments, and getting rid of an outdated payment method shrinks that gap even further.
Automating the reconciliation of incoming payments
Accounts receivable (A/R) also has the incredibly manual task of receiving customer payments and matching them up to customer invoices. This can be as easy as a PayPal payment that’s connected to a native invoice, or as difficult as a paper check in the mail with no account number and a different name than what’s recorded in your invoicing system.
Again, you can use AI to ingest data from historical invoices to understand how payments have been reconciled before, and to make assumptions about matching them up in the future. Let’s say you have numerous outstanding invoices for each customer.
AI technology can take the data it’s learned from your invoicing history and the information on the banking statement to best match up payments to invoices. And it’s not just for matching up payments - AI can help you find errors like amount discrepancies, incorrect invoice numbers, and mismatched payments to invoices.
AI will transform invoicing for the better.
Detecting invoice fraud, improving cash flow, and automating the reconciliation process are just a few of the ways AI will change invoicing from a time-consuming, reactive set of tasks to a proactive, strategic area of the business. In the meantime, you can start leveraging automation to improve existing invoicing outcomes.
Want to learn more about the future of invoicing? Contact Invoiced for a customized demo.