The blog talks about the benefits of having an automated invoice data capture system in place that can deliver the best results to the businesses. For example, automated invoice data capture can result in savings of up to 80% on the operational costs and shorten the long process cycle time from days to just seconds.
Set processes for invoice data capture
Let’s look at the process that’s set from the beginning for the Invoice data capture. A typical invoice data capture refers to the process wherein the accounts payable team enters the details of an invoice or invoices into an accounting system. This system defined for teams can be a simple maintained paper ledger with detailed records of outgoing payments, vendors that are supposed to receive the payments, and the respective dates for the payments. All this process from the outset might look good for a small shop or a store. But this system or set process gets messier for a large enterprise, or a global corporation that comes into the picture.
When we talk about Paper or Paper trails, we no longer need to take the literal meaning of “paper” in this context. Although paper trails are always going to be an important source of maintaining transparency in terms of reports and audits. But AP teams can now rely on digitalized mode of using invoice data extraction that provides secured and cost-effective solutions. However, there’s a key observation here that some of the methods in data extraction do need a considerable amount of manual labor despite having a unified automated option available.
Methods of invoice data capture
As we know there are three methods or rather ways of collecting data from invoices: manual data entry, using a template-based OCR software, and an AI-based automated OCR solution.
All these methods have been in the system of use for a long time by AP teams in their respective companies but over the years the evolution of a smart solution (Artificial Intelligence driven) offering has left the first two methods quite far behind. The Accounts Payable teams have now become smarter and more productive with the usage of an AI-driven solution that is much faster and accurate at its core. Having said that, AP teams are still needed in the loop and by optimizing a smart solution does not mean it is taking away the jobs of the AP staff.
Manual data entry
Manual data entry is a very traditional method of invoice processing that has been used in the past and there are still plenty of AP teams around the world relying on the same. It’s a method where the AP teams look at the digital paper-based invoices in the form of PDFs, excels, and images to manually enter the PO number into the header field for PO number in the respective accounting system. The process sticks to the same while doing other critical entries like Vendor name and amount, etc. Day after day the AP member copy-pastes the entire invoice details into the accounting system with tremendous amount of time being consumed.
Manual date entry in any form or context is a tedious task regardless of whether the companies do it in-house or outsource it to some other company to do the same. The most common disadvantage of having a manual entry driven AP function is that it’s prone to errors. Manual entry driven invoice data capture has always been the method that creates a huge problem for the AP teams that includes late payments, duplicate payments, and friction with vendors.
When OCR (Optical Character Recognition) came to the rescue for the AP teams it created a huge impact in the space of data extraction. OCR tools help the AP teams to scan, read, and collect data from electronic documents and store in the respective accounting system. It reduces tireless and tedious man-hours spent on invoice data extraction and shortens the overall processing cycle.
There are two variants associated with OCR. One is the template-based OCR and the other is the automated AI-driven smart OCR. Template-based OCR requires a good amount of manual effort to process the invoices and prevent errors, but the latter one offers the solution of having an accurate and efficient zero-touch AP process.
Template-based OCR as the name suggests is the process wherein there are certain predefined rules and templates used by the OCR software for reading and capturing the invoice data. There’s still a myth revolving around the AP teams in the companies that this is an automated process and is the best way to extract data from the invoices into the accounting system with minimum manual effort. Sadly, that’s far from the truth. Template-based OCR did come a long way in providing a digitized invoice processing solution to the AP teams but there’s a lot of tedious and manual efforts needed by the staff to really take the optimum utilization of the OCR technology.
Template-based OCR needs the AP staff to create and train the OCR engine every time there’s a new format of invoice that has been received. It works on predefined templates and creating rules for every format becomes a tedious task for the AP teams as well. In simple terms, the software reads the characters in different layouts that has been trained to understand.
It becomes a feasible solution for the AP teams if the vendors submit invoices with the predefined layouts. However, if the AP teams need to process these invoices in a different format, then it becomes a tedious process all over again. These templates are hard to create and maintain and need dedicated staff to do these tasks. This defeats the purpose of automation.
AI-based Smart OCR
As the name suggests, Artificial Intelligence-based OCR software is smart enough to understand and process the data it extracts from invoices or financial documents. With the help of Ai technologies, like Computer Vision, Fuzzy Logic, Natural Language Processing and Machine Learning technology, the software helps recognize and capture relevant information in various document formats with continued exercise of usage. AI-based OCR software completely eradicates the need for developing new templates every time the AP teams receive a new invoice in another unrecognized format.
AI-based smart OCR software solution coupled with business rule engine and workflow automation help the AP teams to completely automate the data entry process. This also creates an opportunity for the AP teams to go touchless or enable zero-touch accounts payable processing. However, the organization human in the loop to keep an eye on the accuracy and smooth running of the overall functioning.
A template-based OCR solution may seem like an obvious advancement for the AP teams to look at if they are completely manual. Having said that, upgrading to an AI-based smart OCR solution would always be the winner when it comes to providing an overall benefit to the AP function and the organization choosing the same. Some notable benefits from choosing an AI-based AP Automation solution is:
- Reduced operational costs by up to 80%
- Improved invoice processing cycle time from weeks to seconds
- High data extraction accuracy by up to 99.5%
- Detection and prevention of Accounts Payable fraud
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.
Schedule a demo with us today to find out more.
About the Author
Himanshu Naidu, Product Marketing, Kanverse.ai