AI is opening a vast landscape of opportunities with immense growth potential for modern-day businesses. AI-powered invoice processing automation platform often harnesses the power of automation, flanked by AI to build game-changing resilient business workflows for the enterprise of the future. It also paves the way for Enterprise 2.0: that drives faster task resolution rate, cost reduction, and turbocharges productivity.
The first step to successfully automate invoice processing is to identify silos; it is mostly formed by employees engaging in time-consuming manual activities. Subsequently, evaluating the possibility of automating the manual processes is also required. An accounts payable workflow is also plagued by silos, where employees often spend much of their time manually processing documents and then entering the data into the enterprise storage system. The siloed operational mentality impacts operations by hampering employee morale and adversely affects productivity. It often ends up contributing to the overall failure of a company or its products and culture.
If you are like most accounts’ payable managers, and you are constantly seeking to understand the best practices for accounts payable invoice processing automation projects - Then this is for you. Learn about the major 5 Reasons why you must automate your accounts payable workflow process. It also will give you a detailed understanding about ways to streamline and automate your AP process workflow.
To overcome these silos, many organizations have adopted account payables automation software and AI document extraction processes to capture and extract data from invoices which feed it into the AP workflow. Then eventually, publishing the data into the enterprise's system of record.
Challenges with the traditional data extraction technology for invoice processing
Traditional platform driven invoice processing software uses OCR (Optical Character Recognition) extraction technology to extract data from invoices, this approach relies on templates for extraction. It leads to extremely low extraction accuracy and numerous unwanted errors emerge. Operators also need to create templates based on invoice data structure to extract the data successfully. The template creation process is painful and takes a lot of time. Traditional OCR extraction solutions struggle to extract data from handwritten invoices; as a result, extraction accuracy is highly affected, and the solution cannot be trusted.
AP teams process numerous invoices from various vendors; manually creating new templates to accommodate every new invoice structure witnessed in the system is an inefficient approach towards digitization goals. Low data extraction accuracy and the painstaking manual template creation process are significant bottlenecks for any AP team.
Learn how Fellowes Brands, a global manufacturer of office and technology accessories, has 17 international subsidiaries, witnessing a massive influx of invoices to the tune of 100,000 documents – Achieved seamless invoice processing automation with Kanverse.
AI (Artificial Intelligence) powered invoice processing workflow
Combining accounting and finance automation initiatives with the new generation of automated invoice processing automation technology that uses AI and machine learning models to extract data from invoices. It ensures high extraction accuracy and eliminates the painful template creation process. It can intelligently recognize the invoice's overall structure to extract all the meaningful field and line-item data. Advanced machine learning technology helps the system to identify specific patterns in the invoice as well.
Using AI for invoice processing workflow automation frees up agent time as extraction accuracy is increased, and manual creation of templates becomes unnecessary. It contributes to an increase in AP team productivity, saves cost and time.
Also Learn how Kanverse combines multiple AI technologies (Computer vision, ML, NLP, fuzzy logic) with OCR to automate invoice processing and is now a preferred technology for digital transformation projects where companies want to inculcate data-powered decision-making into downstream functions. In addition, process owners can achieve a touchless invoice processing experience, agnostic of inbound invoice type with Kanverse.
Computer vision helps AI-based models extract and understand the text from documents. Vision models identify the semantics and apply the correct taxonomies to the inferred data – which addresses entities, determines intent and context, and categorizes the extracted data.
Machine Learning (ML) helps to process documents faster and it also ensures data extraction happens with high accuracy; it also reduces error rates. The ML model complements other
Business processes witness documents in different languages; processing these can be challenging. Natural Language Processing (NLP) makes it easier for enterprises to process documents in different languages – it can seamlessly process documents in over 200+ languages
Using an accounts payable automation software powered by multiple Artificial Intelligence (AI) technologies - helps businesses to streamline invoice processing. Advancements in artificial intelligence technologies are helping organizations attain a remarkably high data extraction accuracy from invoices
AI-powered smart decision making for invoice processing
AI powered Invoice processing platforms greatest strength is its ability to provide an automated stream of intelligence across the Account Payable automation workflow. It helps the AP teams to align their operations based on changing business requirements.
AP process owners can now have the holistic visibility of their workflow. Invoices are seamlessly routed to approvers powered by AI. It also helps to enforce robust monitoring and compliance standards across the invoice processing cycle.
Building an AI-powered invoice processing workflow helps AP process owners make better decisions. It provides practitioners with real-time visibility across process health, document pipeline, error rates, staff productivity, accruals and liabilities, and other critical key performance indicators. AI empowers process owners to quickly identify bottlenecks and fastens exception handling by identifying the root cause and paving the way for faster resolutions.
Learn from Karan Yaramada (CEO and Founder – Kanverse.ai) about how enterprises can leverage AI to make Document Processing Touchless.
RPA enhances AP workflows through automation
Leveraging AI, RPA enhances AP workflows through automation, compliance, intelligent routing, and real-time insights, paving the way for a touchless document processing approach.
Kanverse brings you the best optical character recognition software to automate Accounts Payable (AP) Invoice processing for enterprises right 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.
Schedule a demo with us today to find out more.
About the Author
Aritro Chatterjee, Product Marketing, Kanverse.ai