Technological advancements in artificial intelligence (AI) have made it possible for businesses to unearth meaningful insights from unstructured documents more efficiently than ever.
A growing number of modern enterprises are embracing intelligent document processing (IDP) — a technique that leverages AI technologies such as natural language processing (NLP) and machine learning (ML), to transform unstructured and semi-structured data into usable information.
It’s certainly a step in the right direction. Companies must take advantage of AI-powered data extraction tools to process documents efficiently. It’s faster, more cost-effective, and more scalable.
Structuring the Unstructured Data
Every business document has a different pattern, layout, and terminology. One vendor invoice’s “settle the invoice within 30 days” is another’s “payment is due within a month”. Even documents from the same vendor may differ in format and structure.
All these files, including contracts, invoices, lease documents, and utility bills, contain unstructured data that needs to be captured, structured, cleaned, sorted, validated, and loaded to a data repository for reporting and analysis.
Intelligent Document Processing
Intelligent document processing has garnered so much attention so fast because it enables enterprises to automate the manual process of unstructured data extraction that previously took extensive business resources.
An IDP solution utilizes cognitive capabilities like deep learning and NLP to recognize meaningful patterns in documents and extract relevant information. It allows businesses to capture data from invoices, emails, PDFs, receipts, and various digital documents, which can further be validated and stored in a database for analytics and reporting.
How Does Intelligent Document Processing Work?
Intelligent document processing leverages an AI data extraction technique that identifies similarities between data through a pre-defined criterion. ML and NLP algorithms identify relevant datasets and turn them into usable data. It may include everything from names and addresses to invoice amounts and vendor profiles.
The robotic process automation technology leads to greater flexibility and scalability in document processing, with minimal to no manual intervention.
As a result, enterprises can fast-track their document processing tasks. Many industries — including healthcare, finance, and legal, to name a few — are using AI data extraction to find insights as well as identify discrepancies and errors in unstructured documents.
The insurance sector is among the top industries reaping benefits from AI-driven technology on a large scale. Capturing unstructured data from contracts and forms to automate the KYC (know your customer) process is a great example of how IDP is transforming insurance.
Intelligent document processing can be leveraged in practically every department and industry to structure unstructured data efficiently and effectively.
Key Factors to Consider
Here are some key factors to keep in mind to ensure you pick the right end-to-end intelligent document processing solution for your organization:
- Deployment Time
The faster an organization can extract data from the unstructured document and derive insights, the quicker cost savings can be realized. An IDP solution that supports reusable templates would allow faster document processing at scale.
- Data Accuracy
AI-powered data extraction tools that don’t deliver on accuracy can do more harm than good. Inaccurate and poor data can result in incorrect decisions, ultimately hurting your business performance. So, having data validation functionalities is imperative to ensure accurate results.
Having an accurate and robust data extraction solution that can amp up the BI initiatives is imperative for positive results, but so is ensuring that the solution is scalable and can meet the future needs of the company. Having the ability to add more servers quickly is a big plus. Ideally, you may look for an IDP solution with cloud connectivity to future-proof your investment.
An Intelligent document processing solution should offer great flexibility in unstructured data extraction. Users should be able to extract relevant fields, add new fields to enrich datasets and delete existing fields to take out only helpful information to keep structured data clean and crisp.
- Zero-code Environment
A modern AI data extraction solution should have an easy and intuitive user interface. A code-free solution is ideal because it empowers business users with a non-programming background to handle the data extraction process. The reduced IT dependency leads to increased efficiency of business processes.
When it comes to unstructured data extraction automation isn’t an upgrade but a necessity. Almost every organization handles digital files like invoices, receipt orders, pay slips, etc. An automated processing solution makes unstructured data extraction workflows simpler, cost-effective, and more efficient.
Let Astera help you unlock the wealth of information trapped in unstructured data to stay ahead of the competition. Astera ReportMiner, our data extraction solution, simplifies and automates your routine unstructured data management tasks.
Now with AI Capture, you can easily extract data buried in unstructured documents. Powered by AI-driven technology, the latest feature allows you to extract data from PDFs via a single click and structure the unstructured data in seconds.
Once the reusable template is ready, you can use automated workflows to run unstructured data extraction on auto-pilot. This will ensure accurate and seamless document processing, reporting, and analytics across your business.