What methods does your company have in place to prevent duplicate spend? Most modern invoice automation systems can look out for two invoices with the same invoice number, or the same amount, and stop a payment that appears to be a duplicate. But this doesn’t find typos in invoice numbers, duplicates across expense and AP systems, or a number of other scenarios you may not have even considered.
AI can help. When it comes to duplicate spend, AI takes an expansive view, looking across all back-office systems, identifying duplicate spend across multiple payments, and more. By taking advantage of the structured data in your spend systems as well as the unstructured data in your invoices and receipts, you can identify duplicates with ease.
There are several types of duplicates that only AI can catch.
Manual keying errors. Invoice processes often rely on manual data entry, which is error-prone. An employee might mistype the letter “O” as the number “0,” or “SEPT” as “SEP.” These types of duplicates are preventable and common, but wouldn’t be caught by a traditional invoice system. AI can find manual entry errors in invoice numbers or dates that typically fly under the radar in invoice automation systems and flag them for review.
Different supplier divisions. Your company might do business with multiple supplier divisions. These names may be listed separately in your supplier master list, so if you receive the same invoice from these entities, your AP automation system may not detect it. AI can flag duplicate invoices for the same deliverables sent from a supplier’s headquarters and international divisions.
Different company divisions. Similar to the example above, your own company’s internal divisions can create confusion. Each division within your company may have its own AP organization and approvals process, and wouldn’t know if an invoice was already received and paid by a separate department. AI can flag duplicate invoices for the same deliverables that are sent to different divisions.
Overlapping or cumulative. A supplier may send several overlapping invoices. For example, they might send three separate invoices at different amounts (one for $8,500, one for $4,000, and one for $13,200) and then a quarter-end invoice for $25,700. Traditional invoice systems may not catch this, but AI will flag these invoices for review.
Line-level. AP automation systems may not extract line details from an invoice. AI will check for duplicates at the line level and discover that, for example, the same services were included in two separate invoices.
Different AP systems. Maybe you have several back-office systems because of company mergers. When duplicate invoices hit different systems, your company may never know it. AI integrates with multiple invoice automation systems and flags duplicates regardless of which system they’re in.
Duplicate crossover spend. Your company likely doesn’t have visibility across its invoice automation and expense systems. This could cause you to pay twice for the same service if it’s submitted via T&E reimbursement and again via accounts payable. AI flags this so payments aren’t sent twice.
Duplicate expense claim submitted by two different employees. Maybe this is a mistake, or maybe the employees know that expense reports aren’t cross-referenced (especially if they have two different managers, or are in two different departments). Whatever the reason, AI can cross-reference expense reports from any department and flag when the same receipt is found on two different reports.
Duplicate expense claim in the same report. After a long business trip, all the receipts can begin to look alike, and an employee might accidentally submit the same expense twice in the same expense report. AI looks at individual line items and flags any duplicates.
Duplicates can take many different forms and can be difficult to find in a manual review process. To gain visibility into their business spend, many companies have embraced AI to achieve 100% visibility into expenses and invoices. Companies that automate their audit process are able to find errors, fraud, and non-compliant spend before payment.
