What is Intelligent Document Processing?
Automatically extracting structured information from documents like invoices, purchase orders, and contracts is the goal of Intelligent Document Processing (IDP) technology. This is accomplished by a mix of optical character recognition (OCR), natural language processing (NLP), and machine learning (ML).
- IDP is a mixture of OCR, NLP, and ML.
IDP is a useful tool for enhancing the effectiveness of intelligent data processing procedures inside businesses. IDP’s ability to automate formerly manual processes has the potential to increase efficiency, decrease waste, and boost both profits and client happiness.
- Ingestion– Getting the documents into the IDP system is the first stage in the AI document processing cycle. Several methods exist for this, including scanning paper documents and uploading digital ones.
- Preparation– It is necessary to prepare the papers for processing once they have been swallowed. Duplicate records may need to be eliminated, file formats may need to be converted, and naming conventions may need to be standardized.
- Extraction– Extracting useful information from documents using optical character recognition and natural language processing forms the backbone of the IDP workflow. Information like names of customers, invoice numbers, and dates of purchase orders are examples.
- Validation– After data has been retrieved, it must be verified to check for mistakes and make sure everything is there. As an example, algorithms might be used to compare the extracted data to external databases in search of discrepancies.
- Export– Once the data has been checked for accuracy, it may be sent to other programs. The information may be entered into a contract management or accounting program.
- Feedback– Last but not least, the IDP process includes setting up a feedback loop in order to tweak and fine-tune the system’s performance over time. Adjusting the algorithms to better handle certain kinds of documents may be necessary, as may reviewing the outcomes of the data extraction and validation procedures to discover areas for improvement.
The overarching goal of the IDP workflow is to automate the steps involved in extracting and processing data from non-standardized documents like invoices and contracts. IDP may help businesses save time and money by automating these processes, which increases productivity and decreases mistakes.
There is a wide variety of vendors and solutions out there for IDP, and the optimal one for any given use case will rely on specifics like the documents being processed, the desired degree of automation, and the available budget. UiPath, Abbyy, Kofax, IBM Watson, and Amazon Textract are all examples of IDP document processing solutions.
Invoice processing, contract administration, and claims processing are just some of the many uses for their IDP solution. The approach employs AI and ML to minimize human error and maximize precision.
IDP use cases
- Invoice processing– Data extraction from invoices, including invoice numbers, amounts, and due dates, may be automated using IDP. As a result, invoice processing times may be shortened, and the likelihood of human mistakes will decrease.
- Claims processing– Patient information, provider information, and service details may all be extracted using IDP in the healthcare and insurance industries for use in the claims processing workflow. This may simplify the claims-filing procedure and boost accuracy.
- Legal document processing– Documents such as contracts, case files, and legal briefs may all benefit from IDP’s data extraction capabilities in the legal sector. Better than OCR document processing, IDP can read and comprehend the text. This has the potential to enhance the precision with which legal documents are processed by automating previously laborious activities.
- Contract management– IDP may be used for contract management by gleaning information such as dates, clauses, and parties from contracts. This may facilitate the automation of contract administration and boost contractual adherence.
- Finance– Loan processing, client onboarding, and account opening are just some of the banking and financial operations that might benefit from IDP. This has the potential to cut down on mistakes and speed up operations.