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What is Intelligent Document Processing and Examples of Its Application in Business

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In the growing digital age, data and documents are key components of business operations. Businesses must manage and process many types of documents to be able to determine the best step to take in business advancement.

Managing this document is a task that is time-consuming and requires significant human effort. However, with the advent of new technologies such as Intelligent Document Processing (IDE), businesses can increase their efficiency in unprecedented ways.

This article will go over what Intelligent Document Processing is, how it works, the benefits, and an example of its use in business operations.

What is Intelligent Document Processing (IDP)

Before understanding more about Intelligent Document Processing, it is necessary to first understand this technology.

Intelligent Document Processing (IDP) is a technology that combines artificial intelligence (AI) and document processing. In other words, IDP is a tool that enables businesses to obtain data from various types of documents, classify it, extract relevant information, and use it for specified purposes.

IDP utilizes natural language processing technology (NLP), machine learning, and pattern recognition to analyze data rapidly and accurately without taking a long time.

How the Intelligent Document Process Works

We already know that IDP is a sophisticated technology for document processing, so how does it work? IDP works in eight stages, starting from document reception, character recognition, data processing, to data analysis. Here are all of the stages.

  1. Document reception: Physical or digital documents are received by the IDP system via manual upload, email, or direct integration with a computer device.
  2. Document recognition: The IDP system then utilizes Optical Character Recognition (OCR) to extract text from an image or PDF document.
  3. Data processing: Once text has been extracted, IDP processes the data to identify relevant information.
  4. Validation: IDP can validate data against rules previously determined by the company. For example, check whether the invoice number matches the format or not.
  5. Data extraction: To make data easily accessible, validated data is extracted and stored in a database or document management system.
  6. Exception management: Some documents may not be completely processed automatically. IDP has the ability to identify documents that require further attention and redirect them to manual labor.
  7. Integration into the system: IDP can be integrated with other systems, such as financial systems, ERP, or CRM, so that the extracted data can be maximally used in various business applications.
  8. Analysis automation: IDP can provide reports on the performance of the document management process, including statistics such as the number of documents processed, the time required for processing, and the number of exceptions resolved.

The Advantage of Intelligent Document Processing

It’s not technology if it can’t provide benefits. In the context of Intelligent Document Processing (IDP) it can provide various benefits to businesses. Some of the main benefits include:

  • Improve work efficiency: IDP reduces the involvement of humans in the management and documentation processes. This obviously improves efficiency in terms of both labor and time.
  • Minimize manual error: With automation, IDP plays a role in minimizing the risk of manual errors made by humans in data processing. Data accuracy is believed to be more precise and thorough with IDP.
  • Better document management: IDP helps in storing digital documents that are more neatly organized and easily accessible.
  • Better analysis data: The extracted data can be used for further analysis, helping in better decision-making.
  • Scalability: IDP can be easily operated according to business growth without the need to increase human labor.

An example of Intelligent Document Processing implementation in business

Intelligent Document Processing (IDP) can be implemented in various industries and business fields. The following are some examples of its application:

1. Invoice management and processing

The most common example of IDP implementation in business is invoice management and processing. With IDP, companies can automate the processing of invoice information such as invoice number, date, amount, and vendor data.

2. Contact management

Aside from invoices, IDP is also used for managing business contacts. This technology can identify and extract key information from contracts, such as the effective date, important clauses, and deadlines. This way, companies can monitor their contracts more efficiently and avoid potential violations.

3. Human Resources Management

A company can use IDP to automate the employee recruitment process, performance appraisal, and management of employee personal data. This helps reduce the administrative burden on HR departments and allows them to focus on more strategic tasks.

4. Identification verification

IDP can be used to verify the identity of a customer or business partner. With a document process such as a passport, identity card, or license, the company can ensure that the identification submitted is valid and matches the regulations.

5. Management of company information

By automating the indexing and retrieval of information from internal documents, companies can create an information base that is more accessible to all their employees. Information that can be managed with IDP includes salary information, company information, important company announcements, and many more.

Intelligent Document Processing and OCR tools that are useful for business

That is some short information about what Intelligent Document Processing is. Most of us may be wondering what the difference is between this and Optical Character Recognition (OCR).

IDP and OCR are two technologies that are often misunderstood as one technology. Although both have similarities in terms of text recognition, they have significant differences.

OCR is just used to recognize text, whereas IDP can classify different types of documents and take action based on the information successfully extracted.

The best example of OCR and IDP recently is Fintelite’s OCR+ product. OCR+ Fintelite can extract physical data into digital data and then process it into business data that is useful for business analysis.

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