Businesses are facing immense pressure to do more, and do it faster, across all industries. More organizations are focusing on improving experiences for customers and employees to retain talent and increase revenue.
One way businesses can overcome this pressure to do more faster, is to implement new analytic technologies such as IDPA. What is IDPA though? IDPA stands for Intelligent Data Processing and Automation.
In this blog, we’ll cover what IDPA is, how it works, why it’s important, and what outcomes to expect.
What is IDPA?
Intelligent Data Processing and Automation (IDPA) helps transform unstructured or semi-unstructured data into usable information.
IDP uses AI-based technologies such as Natural Language Processing (NLP), machine learning (ML), and computer vision, to capture, extract, and analyze data from emails, PDFs, images, and other unstructured/semi-unstructured data sources.
This process transforms the data into usable information for businesses to now turn into actionable decisions.
How Does IDPA Work?
IDPA begins with the rethinking process, it then targets modern, AI-based document processing to make the content immediately available and actionable exactly when and where it’s needed.
Intelligent document processing can be done using a variety of AI-based technologies like NLP, ML, and computer vision algorithms. Typically, it follows this process:
1. Categorize and extract the layout and structure faster.
Advanced automation is a faster and more accurate way of extracting relevant information from unstructured and analog data. It builds upon the rules-driven processes built into document processing algorithms.
2. Processing and extracting document information.
Optical character recognition (OCR) scans documents for typed text from manual documents and transforms it into usable data. Intelligent character recognition can detect standard text as well as various fonts and styles of handwriting. IDPA can transform various forms of data structures and apply the data to business applications or workflows.
3. Increase data accuracy.
OCR technology can be error-prone, which means extracted data may need manual review. ML enhances document classification, information extraction and data validation to improve processing quality and reliability. Using low code supervised training within the workflow aims to improve accuracy overtime without having to reprogram extraction rules.
4. Enhance security, reduce cost, store documents and the collected data.
The final document is stored in a format that allows it to integrate with current applications. IDP stores documents and personal information in a secure and digital location. This is especially important for financial and healthcare industries, due to compliance and security regulations. The cost is reduced because automation shortens the processing time which decreases operational costs and better utilizes employee time.
Why is IDPA Important?
IDPA delivers significant benefits on both counts. IDPA saves time, money, and reduces the risk of costly errors by applying document processing that closely supports the way humans understand and manage content.
Employees gain back time and energy from the would-be-tedious tasks of reading and manually processing documents, all while customers benefit from greater efficiency in document-based processes and decisions.
Outcomes of IDPA:
- Direct cost savings by reducing expenses and cutting costs to process large volumes of data
- Easy to use and allows businesses to get set up faster and automate more processes
- Accuracy uplift – see immediate significant increases in data accuracy with the use of AI
- Higher straight through processing (STP) – minimize the need for knowledge workers to manually process documents
- Process efficiency – enables end to end automation of document centric process
- Strategic goal boost –automated data processing supports business goals like improving customer experience
Implement IDPA into your everyday time-consuming tasks today
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