Optical Character Recognition (OCR) has been in use since a long time for simplifying the task of scanning and editing the documents. The purpose of having an OCR solution in place is to get a string of characters from the scanned documents which can be used for multiple purposes. Even though OCR software can easily pick up the text from the documents, it faces the challenge of its inability to make sense of the scanned text. Businesses nowadays require an intelligent system which can help in automating the task of extracting the data from the documents.
An intelligent data processing system can solve the challenges of extracting the data from the invoices, payment orders and payment receipts, thereby reducing the reliance on human resources and eliminating the errors. As industries are growing, there is an urgent need to automate the manual tasks and OCR alone cannot be fruitful. The businesses today have moved to intelligent data extraction and processing which uses artificial intelligence and machine learning to create a self-learning mechanism.
Intelligent Data Processing (IDP) vs. The Traditional OCR Solutions
Optical Character Recognition software works by scanning the documents and creates a string of text and dumps it. The software is not intelligent enough to create a meaning of each word and cannot be used to specifically find any text field like invoice number or particular seller details in the extracted text. Data extraction through OCR requires 100% human interference for text interpretation.
With IDP, the extracted data from OCR can be interpreted to form the meaning of the text using the data interpretation methods like natural language processing and computer vision. The technology enables to extract the data from the unstructured documents and makes the process deliver data for actionable insights and analysis which otherwise is not possible with OCR. IDP can reduce human interference by 25% and result in error-free data extraction.
How does Intelligent Data Processing Work?
Klearstack is an intelligent data processing tool that works with Optical Character Recognition (OCR), natural language processing, and artificial intelligence to extract the data from the unstructured documents.
OCR works on the scanned documents by recognizing the text within the images, hand-written, printed and typed documents and converting them into machine-encoded texts. Pattern and feature extraction methods help OCR in extracting the data from these documents.
The only challenge with the OCR technology is, it is incapable of determining the meaning of the extracted text and to substantiate that artificial intelligence and machine learning are used.
Natural Language Processing (NLP), a machine learning method, works with the text extracted from the OCR and assigns meaning to the words. Thus making computer interpretation of the document possible.
Artificial intelligence works brilliantly to eliminate human errors and capture the documents to create structured texts and reports. The system works on a self-learning model which increases the accuracy of data extraction and interpretation by learning from the previous models. The AI-supported OCR is used in multiple industries that are heavily reliant on paper-based invoices and payment orders for intelligent data extraction with minimal errors and reducing the turnaround time.
Benefits of using IDP Over Traditional OCR Solutions
Intelligent data processing can help overcome the businesses facing the challenge of manual data entry and provide benefits like
Reduced Overhead Expenses
As the data extraction becomes automated and efficient, the reliance on human resources for manual entry and validation can be reduced and the resources can be aligned to other critical business processes.
As the documents are extracted automatically using artificial intelligence, it becomes easier for the auditing teams to check for the relevancy and consistency of the data. The industries with a large number of documents can be benefited with reduced auditing time and efforts.
Intelligent data processing increases the productivity of the accounts department by reducing human errors, eliminating reworking on the invoices, and saving time and resources on the processing. As human interaction is less, more documents can be processed in less time.
By adopting Klearstack, it becomes easier to search for the relevant information amongst the plethora of documents. The extracted data can be easily sorted to get the relevant results. The process is faster in comparison to the old techniques of visiting the individual documents to search for specific information.
Improved Customer Relationship
Quick processing of the invoices and faster execution of services to the customers and suppliers improve the brand image and helps in establishing a cordial relationship.
Klearstack’s advanced data extraction and processing technology can help the businesses and departments with paper-based documents to automate their processes and reduce human interference by 20-25%. To know more about OCR and Klearstack’s solutions, Download the free e-book today
It’s high time that organizations across all domains and irrespective of the organization size should adopt such AI based tools to reduce the wastage of resources and leakages in the cash-flow.