There are two underlying reasons why invoice capture has become an essential tool for companies in recent years. First and foremost, invoice capture contains two powerful and effective technologies, which serve companies to easily automate processes. These are Optical Character Recognition (OCR) and machine learning. The other reason is that by automating one of the most time consuming and critical processes, invoice capture promises high ROI rate.
Invoice Capture Combines OCR and Machine Learning
Invoice capture (also called invoice extraction or invoice OCR) means extracting data from invoices so that invoice processing can be automated. It is significant to automate data extraction and invoice processing because there are tones of different invoice formats and these formats involve many unstructured and nonuniform data types.
Using OCR (and also ICR) to recognize invoice content and machine learning to understand the context of that content and validate each data and item makes the difference. In this sense, invoice capture goes beyond OCR. OCR by itself is incapable of automating invoice extraction, because it needs templates and rules to work properly. This means that every time OCR meets a new format, a different line item, complex tables or a low-quality invoice a human operator’s supervision is necessary.
How to Choose Invoice Extraction Solution?
We can classify invoice extraction solutions under 3 groups:
- Template based solutions. (OCR level)
- Pre-trained machine learning solutions. (OCR + machine learning)
- Continuous training AI solutions. (OCR + machine learning + AI)
The last group is your best choice to fully automate invoice processing, for the reason that these solutions are; format/document agnostic, can learn by themselves, have very high data confidence ratings.
High ROI of Invoice Capture
Companies processing 300-500 invoices/month and whose invoice processing is not automated yet can reach to a $1500-2000 cost saving amount per month. *
*This calculation is based on various variables and therefore may differ from company to company. We took APQC benchmark report data as an average.