Understanding Intelligent Document Processing (IDP)
Intelligent Document Processing (IDP) is a technological solution aimed at sorting structured data from various documents like contracts, invoices, and purchase orders. The powerhouse behind IDP includes machine learning (ML), natural language processing (NLP), and optical character recognition (OCR).
IDP marries the power of OCR, NLP, and ML to boost the efficiency of intelligent data processing within organizations. It's renowned for its potential to automate manual tasks, leading to increased productivity, reduced waste, and enhanced customer satisfaction and profitability.
Unpacking the IDP Workflow
- Ingestion: The AI document processing cycle commences with feeding the documents into the IDP system. These can either be scanned or digitally uploaded.
- Preparation: Once absorbed, documents need to be prepared for processing. This often involves removing duplicate records, converting file formats, and standardizing naming conventions.
- Extraction: The strength of IDP workflow lies in applying OCR and NLP to draw useful data from documents. Info such as customer names, dates of purchase orders, and invoice numbers are typically extracted.
- Validation: After data recovery, it's scrutinized for errors and completeness. For instance, algorithms might compare the drawn data against external databases to spot any inconsistencies.
- Export: When the data passes the validation stage, it's forwarded to various applications such as accounting or contract management programs.
- Feedback: The final phase in the IDP process entails establishing a feedback loop to help refine the system's performance. This can involve adjusting the algorithms or reviewing data extraction and validation outcomes to identify improvement areas.
The primary aim of IDP is to automate the process of data extraction and processing from non-standardized documents, such as contracts and invoices. This paves the way for increased productivity, reduced errors, and significant time and cost savings.
IDP Solutions and Use Cases
Numerous providers offer different IDP solutions, but choosing the best one depends on the specifics of the documents to be processed, the level of automation needed, and the budget. Well-known providers include UiPath, Abbyy, Kofax, IBM Watson, and Amazon Textract, among others.
Their IDP solution finds use in various areas like invoice processing, contract management, and claims processing. As it relies on AI and ML, it notably reduces human error and increases accuracy.
IDP Use Cases
- Invoice Processing: IDP can automate data extraction from invoices, reducing processing times and minimizing errors.
- Claims Processing: In the healthcare and insurance sectors, IDP is used to extract information like patient details, service details, and provider information, simplifying the claims process and enhancing its accuracy.
- Legal Document Processing: IDP excels in extracting data from documents like contracts, legal briefs, and case files in the legal field. It goes beyond OCR document processing to read and understand the text, enhancing the accuracy of processing legal documents.
- Contract Management: IDP can draw data such as clauses, dates, and involved parties from contracts, automating contract management and enhancing contractual compliance.
- Finance: In the banking and finance sectors, IDP can speed up procedures and reduce errors in tasks like loan processing, customer onboarding, and account opening.