AI Driven Accounts Payable Transformation
Tarun Tater, Neelamadhav Gantayat, Sampath Dechu, Hussain Jagirdar, Harshit Rawat, Meena Guptha, Surbhi Gupta, Lukasz Strak, Shashi Kiran, Sivakumar Narayanan
[IAAI-22] Deployed Highly Innovative Applications of AI
Abstract:
Accounts Payable (AP) is a resource-intensive business process in large enterprises for paying vendors within contractual payment deadlines for goods and services procured from them. There are multiple verifications before payment to the supplier/vendor. After the validations, the invoice flows through several steps such as vendor identification, line-item matching for Purchase order (PO) based invoices, Accounting Code identification for Non- Purchase order (Non-PO) based invoices, tax code identification, etc. Currently, each of these steps is mostly manual and cumbersome making it labor-intensive, error-prone, and requiring constant training of agents. Automatically processing these invoices for payment without any manual intervention is quite difficult. To tackle this challenge, we have developed an automated end-to-end invoice processing system using AI-based modules for multiple steps of the invoice processing pipeline. It can be configured to an individual client’s requirements with minimal effort. Currently, the system is deployed in production for two clients. It has successfully processed around ~80k invoices out of which 76% invoices were processed with low or no manual intervention.
Introduction Video
Sessions where this paper appears
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Poster Session 4
Fri, February 25 5:00 PM - 6:45 PM (+00:00)
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Poster Session 8
Sun, February 27 12:45 AM - 2:30 AM (+00:00)
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