Enterprises have witnessed the transformative benefits of automation with its deployment across multiple business processes, including automating invoice processing Accounts Payables (AP). However, the whole context of automation changed with the introduction of Artificial Intelligence (AI). Efficient management of accounts payable and management is vital for a business as it allows an organization to handle its finances effectively.
Native Invoice Processing Automation Challenges
Native invoice automation technology is a rule-based system, i.e., the system performs the tasks based on predefined criteria. However, enterprises must be mindful that rule-based process automation fails in several instances. One key area is when the system fails to extract data from invoices accurately. It happens commonly with AP teams, as they witness invoices bearing diverse types and formats - ranging across multi-invoice, multi-page, scanned, and invoices in PDF, JPEG, formats, etc. Also, rule-based automation cannot determine fraudulent transactions, and the risks of AP fraud remain high. On the other hand, AI-powered workflows deliver actionable decision-making insights on a real-time basis to business teams which traditional automation cannot.
Download this E-Book to learn about the benefits of AP invoice automation. Automate high-volume, repetitive manual invoice processing tasks and improve overall process efficiency and organizational productivity!
Zero-Touch Invoice Processing Automation With AI
AI for Invoice automation entails intelligently digitizing the entire document processing workflow across the Accounts Payable department. It is achieved by eliminating manual touchpoints that require human intervention. Kanverse Hyperautomation platform helps enterprises to build zero-touch invoice processing workflows. With the help of powerful AI technologies invoice processing can now become touchless - recognize, classify, capture, and extract data from inbound invoices without manual intervention.
Download the E-Book to find out about the role of AI in invoice processing which enterprises should be mindful of before considering automation.
Kanverse then passes the data through an intelligent business rule framework. It ensures that the data is reconciled appropriately and then organizes the information based on business needs. The extracted raw data is now validated and verified. Then, the system automatically exports the data to downstream business applications. The entire process is powered by multiple Artificial Intelligence (AI) technologies to make business processes more resilient to disruptions and help mitigate risks.
Kanverse AI automation combines multiple AI technologies (Computer vision, ML (Machine Learning), NLP, fuzzy logic) with OCR (Optical Character Recognition) to derive insights from unstructured documents. As a result, it has become a preferred technology partner for digital transformation projects where companies want to incorporate data-powered decision-making into downstream business functions. In addition, business owners can attain a touchless invoice processing experience, agnostic of inbound invoice type with Kanverse.
Learn more about how enterprises can achieve zero-touch Invoice Processing across Accounts Payable department.
AI Powered - Invoice Processing Automation Components
AI-powered OCR – Optical character recognition (OCR) technology is a critical automation component that enterprise-grade software uses to extract data from an invoice (scanned or image) sent by the vendor. The extraction technology used by OCR follows a template-based approach for extraction – it can only extract data from similar documents. Native OCR tech fails to extract data from multiple types of documents.
AI-powered OCR solutions change the data extraction dynamics – it extracts data from a wide range of invoices with up to 99.5% accuracy. The extracted data is also translated into a machine-readable format to make it accessible to AP teams for editing, searching, or future referencing purposes.
Enterprises need to handle several types and forms of documents daily. Automating processing of the data is usually done using OCR technology. Learn more about OCR technology.
AI-Powered Document Capture and Classification – AI for invoice processing leverages a data capture automation software that comprehends and contextualizes data from incoming invoices. It then identifies the critical data and extracts it from inbound invoices of any forms (paper or electronic versions) - without any human operator's guidance.
Documents that enter business processes are often groups of pages that contain distinct types of operational information. Document classification is a crucial step before processing as it identifies and separates the relevant ones for processing. It accomplishes it by listening in across multiple channels - from where it can identify the invoices for processing and discards other documents. Automating invoice processing ensures that the system can seamlessly recognize and understand the information within an invoice.
AI-Powered Data Extraction – Having AI for process optimization ensures high data extraction accuracy while processing invoices. It is essential as it reduces errors and eliminates manual intervention. High data extraction accuracy ensures that the software is correctly comprehending the invoices. It is achieved by training the AI modules based on existing invoices. Computer vision identifies the invoice semantics just like a human operator and successfully extracts specific data elements like dates, names, numbers, etc.
Auto Learning – With Auto-learning, AP teams can now process and train new invoices simultaneously - by choosing to enable/disable training mode. With Kanverse, users can now capture and resolve extraction ambiguities from new document types and automatically schedules them for learning purposes. The system automatically evaluates the newly trained model to ensure that it meets key performance parameters. Advanced AI powers auto-learning, that optimizes processes, prevents similar document processing errors on new document sets, saves operator time, and increases productivity.
Learn about auto-learning and why it matters for document processing teams.
Natural Language Processing (NLP) – NLP technology is helpful to interpret and comprehend human language, both in the form of text and speech. NLP helps to classify human utterances and perform a wide range of activities. NLP technology has multiple use cases - It allows AP teams to process invoices in multiple languages - which is extremely helpful for enterprises with global operations.
AI-Powered Data Validation – AP teams can solve invoice reconciliation and data validation challenges with Kanverse's intelligent business rule framework. It ensures zero-touch invoice processing. Passing the data through the intelligent business rule framework eliminates the chances of errors and prevents incorrect data from entering systems of records. Intelligently perform 2-way and 3-way matches - by matching invoice details with the purchase order (PO), verifying extracted data with residing ERP (Enterprise Resource Planning) systems data, validating payment terms and site code, etc. It frees employee time, reduces error rates, optimizes process operations, and increases productivity. It also eliminates the scope of duplicate payments for an invoice.
Kanverse Accounts Payable Invoice Automation digitizes document processing for enterprises from ingestion, classification, extraction, validation to filing. Extract data from a wide gamut of documents with up to 99.5% accuracy using its multi-stage AI engine. Say goodbye to manual entry, reduce cycle time to seconds, optimize cost by up to 80%, minimize human error, and turbocharge productivity of your team.
AP automation software like Kanverse APIA (AP Invoice Automation) is built to do the heavy lifting across your AP cost centers while your staff can focus on productive and business-critical activities.
Kanverse can also automate insurance submission workflows and seamlessly process ACORD and supplemental forms.
Schedule a demo with us today to find out more.
About the Author
Aritro Chatterjee, Product Marketing, Kanverse.ai