There are industries that generate thousands of documents every day which have important information to be captured and can be used for analysis and other purposes. With the advent of Optical Character Recognition software in the 1990s, it became quite easy to extract and store information from multiple files and sources that reduced the manual efforts of the industries.
As technology has advanced over the years, the focus has shifted to Intelligent Data Extraction which involves not just capturing the data from the sources but carefully analyzing it and creating meaning out of it. With the help of Intelligent Data Extraction, text can be extracted from digital assets like documents, emails, text files, scanned images, structured and unstructured data, and made available in usable formats with the help of defined rules and data extraction templates.
As the information generated by an organization is available mostly in an unstructured format, accessing that information requires a robust technology that can process the documents with minimal human intervention. The OCR document scanners used by the organization are not completely reliable and require 100% manual efforts to interpret the text read by OCR.
Intelligent Data Extraction uses artificial intelligence to capture the data from the documents and streamlines it into a piece of resourceful information through the extraction process. It serves as a single tool to extract information from any kind of document and helps optimize the business processes.
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How Does Intelligent Data Extraction Work?
Traditional OCR limits itself to identifying characters and dumping the extracted data in a document. These solutions aren’t capable of making sense of the data extracted hence the end result is in unstructured format that needs complete human intervention.
Artificial Intelligence techniques like Natural Language Processing (NLP) and Machine Learning (ML) allow the solution to contextually understand the meaning and optimal usage of input (text, numbers and special characters). Thus, the system becomes capable of organizing the data in a structured format by mapping the values to their keys. The end result is a structured document that is ready for analysis with just 20-25% human intervention.
Hence the term Intelligent Data Extraction and Recognition. You can then run rich analytics on such data. You can now even automate the processes that contain unstructured documents.
We are in the stage where we achieve the end results with machine-human collaboration (human-in-loop) and as the algorithm matures with more data we can expect to achieve up to 90% accuracy. Here are some things we can do with Intelligent Data Extraction Technology:
- Convert your documents into structured data
- Make your processes automation ready by using this structured data
- Derive actionable insights and data analytics on top of your unstructured documents, without much manual intervention
- Run automated rich text data analysis like Sentiment Analysis, Contextual Analysis, etc.
Applications of Intelligent Data Extraction in Different Industries
There is a range of industries that can utilize the benefits of intelligent data extraction and can upscale with the help of optimized data extraction processes. Some of the industrial applications of Intelligent data extraction and processing are listed below:
Healthcare:
It is one of the industries which has a heavy reliance on data and generates thousands of documents every day. As the EHR (Electronic health records) and EMR (Electronic medical records) are becoming much more important in the context of keeping the health records of the patients, data extraction using artificial intelligence can be of prime importance in deciphering the patient medical records and making them available instantly with the help of intelligent document processing. It can help in providing personalized care to the patients by providing immediate access to the health records of the patient to the specialists.
In addition, the EMR/EHR data can be handy for insurance claim assessment and during healthcare insurance litigation.
Legal Service Providers:
Legal industry is document-driven and generates a deluge of documents like litigation filing, first information reports, documents pertaining to mergers and acquisitions, articles of association, previous court orders, various kinds of agreements/ contracts and other documents of importance. Storing and retrieving this information can be a tedious process considering the number of documents that arrive every day.
Using the Intelligent data extraction for extracting the information can be highly valuable as it can minimize the errors and discrepancies which cause greater trouble in legal work.
Supply Chain Management
Supply chain industry typically involved in procuring and industry buying faces the challenges of invoice processing and purchase order maintenance as the documents can be in multiple formats with hard to read texts. A lot of human hours are utilized in deciphering the semi-structured documents and feeding them to the ERPs. There are chances of human errors in document processing leading to delay in payments and low quality work as well.
Using Intelligent Data Extraction with OCR can aid in capturing the data from the invoices without much human interference and further assist in purchase order automation. The processes can be streamlined and the human hours saved can be used for other productive purposes.
Accounting and Taxation
Most of the tax work and accounting practices still rely heavily on documents and paperwork. A large number of documents lead to less productivity and reduced efficiency of workers causing more errors in documents processing. The department handles documents like invoices, bills, account receivables, payment information, and export-import details as well. Errors in processing such documents create a risk of late payments and hamper the relationship with the clients.
During the end of financial years the chances of errors, workload and the associated cost of mistakes becomes even more critical with the added burden of tax and GST returns filing. The advanced technology of Data extraction can be used by the accountants to automatically process the documents for invoice data extraction and thus reducing the errors. The advanced receipt data extraction further optimizes the process and helps in storing the payment records safely.
Banking & Finance
BFSI firms are moving towards digital document processing and utilizing the benefits of paperless work but there are departments that use physical paperwork and require constant checks and audits for maintaining the quality work. There is a constant inflow and outflow of invoices and purchase orders from the vendors that are to be entered into the system and with the help Intelligent data extraction technology, the system can be channelized for maximum output and minimum errors.
Intelligence data extraction is an advanced technology that can reduce the workload of the industries which are heavily reliant on paperwork and spend a large number of hours processing the documents. With IDE in place, industries can focus on better opportunities in creating streamlined and optimized work processes.
KearStack is a technology leader and has developed advanced solutions for invoice and payment orders automation and is helping the industries leverage the power of intelligent data extraction with OCR.
Conclusion
Intelligent data extraction 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 guide to Intelligent document processing today!
