Hyperautomation quickly dominates the technology trends of 2022 thanks to its outstanding ability to integrate advanced technology solutions, expand automation capabilities and optimize business operations. In particular, Intelligent Document Processing (IDP) is chosen by many Vietnamese businesses in the hyperautomation journey. So what exactly is IDP and what advantages can this intelligent technology bring to organizations?
What is IDP?
IDP is the technology of automatically collecting, extracting, and processing data from a variety of document formats, from unstructured data or semi-structured data.
IDP applies Optical Character Recognition (OCR), Artificial Intelligence (AI), including Natural Language Processing (NLP), Computer Vision (Computer Vision), and Machine Learning (ML), allowing software robots to read, analyze, classify, extract, and evaluate complex data.
Data is a valuable asset for any organization in the digital transformation journey. However, more than 80% of enterprise databases are encrypted in an unstructured or semi-structured format, such as business documents, emails, images, or PDF documents. This complex data requires smarter processing. Therefore, IDP’s ability to process complex data with maximum accuracy plays a vital role in extending the scope of automation to even sophisticated processes, enabling businesses to optimize operations and approach hyperautomation more effectively.
IDP promises to change the operating process of many businesses. Source: contract.fit
Although RPA and IDP have the same goal of automation, they are two completely different concepts. RPA is considered a comprehensive solution for repetitive tasks, rule-based processes, and structured data. Therefore, for semi-structured and unstructured data, RPA needs the support of the IDP tool to solve more complex tasks. IDP is the next generation of traditional OCR technology, enhancing the ability to process data from complex documents with optimal results.
Hence, augmenting IDP with the RPA platform allows all the processes to run thoroughly, limiting disruption in the deployment process and optimizing the power of automation technology in the enterprise.
How does IDP work?
Not only identifying data, but IDP also includes various essential steps to capture and convert semi or unstructured data into structured data for easy processing.
IDP is optimized to meet the requirements of high-quality data processing. Source: eigentech.com
The critical stages of IDP include:
IDP applies several methods to improve data quality, such as noise removal, binarization, and deskewing.
- Binarization: It is the technique to convert any grayscale image into a black and white image.
- Deskewing: It is a process of straightening a scanned image to improve the results of data extraction and other processes.
- Noise removal: This method aims to remove any unwanted small dots/patches to make texts clearer to IDP.
The Computer vision algorithms in IDP are used to recognize and analyze text fragments and images, both in digital and paper-based forms.
Integrate NLP technology to recognize characters, symbols, letters, numbers, or text in unstructured documents. Using methods such as named entity recognition, sentiment analysis, and feature-based tagging, NLP can read data from complex documents and classify context-based data into text and image documents.
Use Deep learning and ML-based OCR method for data extraction.
Once the data is classified, IDP allows data to be converted into different formats such as JSON, XML, PDF, etc.
IDP leverages a previously formatted database to validate data. At this stage, specific data validation rules are implemented within the document to notice any problems relating to documents.
Hence, any document flagged red is delivered to humans for further evaluation and correction.
The final stage of the IDP process involves integrating data into the enterprise’s existing systems, including the cloud platform or an internal database.
Top 6 benefits of IDP
IDP is considered the solution to data processing and coordination. Source: blog.aspiresys.com
IDP proves its efficiency for organizations that go through a significant volume of semi or unstructured data such as sales orders, invoices, or several back-office processes, like claims processing, collateral creation. Because these documents tend not to be processed effectively using traditional automation software.
Hence, the implication of IDP brings data processing to the next level.
- Fast processing time: IDP reduces processing time up to 85% and increases data extraction speed up to 10 times.
- Boost accuracy and efficiency: The IDP solution can achieve up to 99.9% accuracy, eliminating errors compared to traditionally manual processes. In addition, improved processing times and less human intervention mean significantly improved productivity.
- Save costs: By minimizing the costs associated with manual processes, human resources, and errors elimination, along with fast and accurate data processing, IDP enables organizations to save up to 70% of business costs.
- Ease of use: The IDP solution requires no data science expertise and complicated rules or software installations.
- Drive flexibility: IDP can easily integrate with an organization’s existing platforms and combine effectively with automation solutions like RPA to optimize automation processes.
- Increase employee value: Free up 80% of employees from tedious manual work, enabling higher-value projects.
akaBot (FPT) is the operation optimization solution for enterprises based on RPA (Robotic Process Automation) platform combined with Process Mining, OCR, Intelligent Document Processing, Machine Learning, Conversational AI, etc. Serving clients in 20+ countries, across 08 domains such as Banking & Finances, Retails, IT Services, Manufacturing, Logistics…, akaBot is featured by Gartner Peer Insights, G2, and ranked as Top 6 Global RPA Platform by Software Reviews. akaBot also won the prestigious Stevie Award, The Asian Banker Award 2021, etc.
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