Intelligent Invoice Data Extraction: Cognitive or Template Based? — V2Solutions
What prevails?
Automating invoice processing is probably one of the first steps in transforming and streamlining the Accounts Payable function.
In this blog, we discuss and analyze the different approaches of invoice -extraction technologies that are available today.
- Invoice PDFs hardly have any structural information. Unlike HTML tags, PDFs have no concept of words, paragraphs, tables , etc. It is just pixels and letters and number pixels cannot be differentiated from image pixel s . An OCR system is required to identify letters and number s .
- Invoices are in unstructured and varying formats. graphics, different fonts, background color tables , etc. add to the complexity of automated data extraction. Identifying the invoice layout, invoice layout, locating the invoice fields , and extracting data become difficult.
- Volumes of invoices to be processed is large. Manual effort is not worth it, and the technical solution needs to be feasible and effective. Computer algorithms today are reasonably able to effectively mimic the human brain ‘s cognition in processing invoices , but not without shortcomings.
- Errors in data entry, data extraction , or the three-way matching process with a purchase order (PO) and goods received note (GRN) that impact downstream processes and timelines and introduce payment risks.
- Support for continuous import and export
- Availability of Web APIs, Integrations, and Webhooks to push/pull data
- Extensions that allow modification of the captured field values through an intuitive interface
- Speed — low latency and high throughput. Latency — how quickly the system is ready for data-extraction and completes it.
- Throughput- applies to a large batch of document s .
- Parallel processing of similar invoices
The main technology options for invoice data extraction are :
- Template-based extraction Models: Template refers to implementations that make use of positional vector s to locate and extract data from within a document .
- Template-less (Cognitive — AI/ML/NLP): Also called intelligent invoice data-extraction , the use of AI technologies is to mimic the human mind to the extent possible and learn to perfect data extraction as it keeps on getting exposed to different structures of documents and invoices.
T he principle in invoice data-extraction technology remains the same; i.e., pre-processing an invoice image, locating key-value pairs in the invoice document , and using OCR to extract the key-value pairs. It should offer facilities to export the digitized data in universally accepted format s that can be stored or ported to consuming applications easily .
Comparing the various Invoice Data Extraction Methods
Why Cognitive triumphs over the other options
Cognitive-based data-extraction systems have a higher extraction potential over a range of complex unstructured document types.
- No need to maintain templates. Invoices are received in hundreds of varying formats and keep changing. Maintaining many such templates or even generalizing a combination of invoice-fields into a few sets of templates is practically difficult.
- Key-value pair extraction is more reliable. Cognitive systems use pattern matching regular expression, cognitive vision, and semantic taxonomy structures in addition to Machine Learning and NLP. NLP is used to make sense of context-specific words and phrases.
- Systems can operate with an extremely low level of human intervention. Faster invoice processing enhanced data-accuracy and increased productivity.
Final thoughts
Automating invoice processing till now has been needlessly complicated. Setting up templates takes time, is a continuous process, and needs supervision and maintenance. Keeping track of changes and recapturing invoice data for any audit or dispute-resolution is also difficult. Employees need to intervene to fill in functionality gaps. Cognitive-based invoice processing overcomes deficiencies of a template-based system. Hybrids viz. templates are automatically generated using AI don’t leverage the full potential of AI. These can easily mature into full-fledged cognitive extraction-systems. An automated invoice processing solution that delivers creates operational efficiencies, improves compliance, and provides the basis of more automation opportunities for other types of document processing.
Learn more about how Intelligent Document Extraction benefits your organization in a multitude of ways.
Originally published at https://www.v2solutions.com on December 30, 2020.
