Transforming Invoice Workflows with Intelligent 3-Way Matching

Machine learning, a branch of artificial intelligence (AI), leverages algorithms and patterns in data to optimize and enhance outcomes.

Pairsoft is already utilizing this transformative technology to predict accurate coding and approval workflows, drawing from past invoice data experiences.

What future applications can we anticipate? One intriguing advancement involves 3-way matching, though it requires us to rethink the concept of matching itself.

3-way matching has long been a cornerstone in AP automation, facilitating invoice approvals by comparing three documents – the purchase order, the goods receipt note, and the invoice – to ensure all three align. Typically, this involves line-level matching, where invoice lines are manually compared to their ordered and received counterparts. Any discrepancy halts the process, necessitating a time-consuming investigation. This traditional method, with its rigid rules, often leads to unnecessary exceptions and frustration.

AI enables us to approach this with greater flexibility. The ultimate goals of AP automation are to reduce manual labor, increase accuracy, and simply save money. Let’s explore how we can achieve smarter, more efficient matching:

The conventional method relies on static rules that mechanically block matching, resulting in cumbersome exception handling. With line-level optical character recognition (OCR) and AI, we can identify issues within line items and only flag real exceptions that require intervention. This approach elevates touchless AP automation, allowing us to focus on higher-value tasks with greater financial significance than typical non-matched line items.

Example

Conventional: An invoice is flagged because of a minor typographical error in the vendor's name or address, leading to a time-consuming manual review process. With AI: The AI detects and corrects minor typographical errors by cross-referencing existing vendor information, allowing the invoice to be processed seamlessly.

While system-assisted matching may not suit every business, we challenge the norm by harnessing AI for laborious tasks and allowing users to make the final call. This approach balances automation with human oversight, offering the best of both worlds. Consider the insurance industry, which has used AI for fraud detection in claims processing for over a decade. AI handles the bulk of the work, flagging high-risk claims for human review. This shift happened because manual review of all claims no longer made business sense. AI brings a similar practical approach to AP matching.

Discover more about the benefits of machine learning for AP invoice processing with Pairsoft.

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