Best Practices and Challenges for Document Processing
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Best Practices and Challenges for Document Processing

By CIOReview | Thursday, August 25, 2022

Technological advancements have made document processing seamless. Still, there are specific challenges that come as obstacles during document processing.

FREMONT, CA: Document processing has been significant changes over the last few years. Data can now be entered automatically into databases instead of being manually typed. Many applications of Intelligent Document Processing can save you time, reduce errors, and digitize your documents.

In Intelligent Document Processing (IDP), documents are converted into digital format to make them available for further processing. The first version of this system used optical character recognition (OCR) software to convert the letters and characters in the images into machine-encoded text based on the optical character recognition solutions. The next step was to use an automated platform to accept and process documents. With AI underwriting software, names, addresses, and incomes are detected, inserted, and calculated accurately.

Importance of intelligent document processing system

It is difficult to meet the market's demands and operate effectively as a business if they have to process documents manually. IDP makes processes seamless by automating complex methods, simplifying data entry and validating processes, optimizing and enhancing productivity and scalability, maintaining precision in results, and saving time and effort.

What are the best practices for document processing?

Human intervention is required for technology to work effectively. Let us understand the best practices for document processing.

Documents must be categorized and authored based on their function to ensure accurate data extraction and placement. 

Automation of semi-structured and unstructured data is fluid and concise when converted into structured data. Integrate the data to reach the right people. 

It is important to consult experts to determine how the data will be used and how it should look after the data has been processed. 

Challenges in document processing

In today's competitive business environment, digital transformation has become a must-have rather than a best practice. There are several challenges to consider before converting to digital document processing. 

Complex documents and inconsistent information may not be suitable for this system, as it processes in one format based on predefined extraction rules. Fixing manual review issues requires the expertise of processing experts, which can be time-consuming. Getting to the bottom of common errors that slow the system down is difficult since no transparency is available.

In recent years, document processing platforms have improved, meaning these issues are no longer a concern. For example, machine learning and artificial intelligence continue to evolve, reducing the number of errors.