Manual invoice data extraction is a redundant and slow process that involves collecting the invoices from the suppliers and feeding the details in the ERP for approvals and further processing. Since the last few decades, there has not been much of a technological shift in invoice processing and because of that, the accounts payables department in an enterprise is loaded with a plethora of document-based invoices. Most of the large scale organizations have more than 500 suppliers and manually processing an influx of invoices is a slow and cumbersome process. Due to less visibility and error-prone processing, a lot of time and cost are spent which leads to delayed payments and reworking on the erroneous invoices. To combat the issues involved in manual processing, Artificial intelligence is being used for invoice data extraction to automate the business processes and decrease the turnaround time.
Optical Character Recognition coupled with Artificial Intelligence can simplify invoice data extraction by reading the information in the documents and presenting them in a digital format. It can also pick up on human errors and resolve them to produce a meaningful text which can be analyzed later.
Intelligent Document Processing (IDP) is the process of intelligently capturing the domain-specific data across documents and streamline document routing activities using AI-based methods. Regardless of what kind of document needs to be processed, scanned or native PDFs, structured or unstructured, IDP serves a single purpose: to extract structured information without the need to define rules or templates.
Some of the industrial benefits of using invoice data extraction using AI are discussed below:
Decreased Manual Intervention
In an automated data extraction system, manual intervention is reduced by almost 70 to 80 percent. An Intelligent Document Extraction tech that leverages OCR document scanner and artificial intelligence (AI) can identify the various data types without any need for a specific template and can intelligently read the data and convert it into a digital text. At the end of the data extraction, one can cross-check the details for any errors.
Higher Accuracy of Extraction
Invoice data extraction using AI can reduce errors and increase the efficiency of the system and can deliver faster results in comparison to manual processing. The advanced, deep learning method of data capturing keeps on correcting the errors and becomes highly efficient with time. With the help of AI, more invoices can be processed accurately in less time, increasing system efficiency, and productivity.
Time Saving in Invoice data extraction and Processing
A technology-driven processing system will help in reducing the time required to process a single invoice and the cognitive data capture through Intelligent Data Extraction will shorten the processing cycle resulting in processing more invoices in less time. A well-established system using Artificial intelligence for data extraction can reduce the turnaround time by five times and increases the overall productivity of the system by 200%.
Artificial Intelligence helps in template-less extraction of data from the invoices and there is no need for customization and configuration of rules for the extraction process. This helps in saving the implementation costs, efforts of the accounts departments, and operational expenses on processing the invoices. The increased efficiency of the system and reduction of errors helps in achieving significant returns in a short time.
Efficient Process Management
Invoice data extraction using AI will help in reducing the rework required for erroneously processed invoices, avoids late payments fees and penalties by the suppliers for the left out invoices and reduces the human interference with less approval time for invoicing. An efficiently managed system will improve the relationship with the vendors and help in becoming a result-driven and optimally functioning organization.
How Invoice Data Extraction using AI Works?
Invoice data extraction using artificial intelligence works in a self-sustainable manner to understand the format of the documents being scanned and learning and adapting with time. As there is no particular format followed for the invoices, an AI-powered optical character recognition software is made with the capability to comprehend the data using deep learning, natural language representation, and optical character recognition. The unstructured data is converted into a structured format and can be used either to directly fill the customer forms and bills or on the enterprise resource planning systems for reconciliation with the invoices. The automated processing results in an error-free and optimized data ready to be used for analysis.
Intelligent invoice data extraction using AI can help businesses like finance, banking, and legal with loads of paperwork and invoices to streamline their processes and save the resources on manual invoicing. KlearStack’s artificial intelligence led solutions are created to solve the challenges of the industry and equip them to undertake a technological leap to upgrade the invoicing process and reap the benefits of the highly productive system. To know more about KearStack’s automated invoicing system, download the free e-book today.