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Your Guide To AI Document Analysis

AI document analysis helps businesses to process more documents at greater speeds, uncover patterns within data, combat fraud, and reduce errors.

Your Guide To AI Document Analysis

How Can Your Business Utilize AI Document Analysis?

Data is the lifeblood of many businesses today, with many companies handling millions of documents on a regular basis. AI document analysis helps businesses to consume, extract, and process important information from this large volume of data in an efficient and practical manner. Read on to learn what AI document analysis is and how it is leveraged by modern businesses as part of their regular workflow.

What is AI Document Analysis?

Document analysis technology enables companies to process large volumes of documents that would otherwise require significant time and resources to process manually. As an example, in banking millions of invoices, contracts, mortgage applications and other forms of paperwork are received on a daily basis. To process all of these manually would take significant manpower, be prone to error, and represent a significant expense in terms of both time and budget. Instead, AI is used for data extraction, document insights, and processing content. This increases operational efficiency and allows a business to provide users with a much faster and smoother service.

How does AI Document Analysis Work?

AI document analysis leverages machine learning (ML) and natural language processing (NLP) to perform processing tasks, provide insights, and help automate workflows involving physical documents. Firstly, optical character recognition (OCR) technology is used to identify text on a scanned document, whether it be handwriting or printed text. Early-stage heuristic functions are then applied to quickly determine what type of document it is so that the correct models can be applied to process it. For example, the layout of mortgage application forms likely follow a consistent format. Identifying that format allows the system to slot it into the correct workflow without having to process the entire document first.

What Kind of Industries Benefit from AI-Based Document Analysis?

There are many different use cases for AI based document analysis. Document processing technology allows companies to perform document analysis and process documents as part of automated workflows, slotting in to existing systems and models. The number of industries that stand to benefit from this is virtually unlimited - any business or industry that deals with documents in some form stands to benefit from the features provided by such systems. These industries include:

  • Banking & finance

  • Shipping & logistics

  • Warehousing & inventory management

  • Manufacturing & supply chain management

  • Retail

  • HR & business administration

  • Accounting

  • Insurance

Many of these industries deal with large volumes of documents on a daily basis and each may have separate requirements and needs for handling and processing these documents. Fortunately, a sufficiently mature platform can process thousands to millions of files for both simple and complex use cases.

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What Value does Automating Document Analysis Bring? 

Much like there are multiple use cases for this technology, there are also multiple benefits that it brings to companies that utilize it. Listed below are just some of the benefits automating document analysis brings to companies.

Frees up Employee Time

Manually processing documents is a time and manpower-intensive task. Not only that, it is unavoidable that mistakes will be made along the way, which takes additional time and manpower to track down and correct. By automating these tasks, employees are freed up to perform tasks where they are better suited than AI, such as in creative endeavors or those requiring client-facing interaction, rather than repetitive tasks.

Combatting Fraud

In addition to the regular processing of legitimate documents, AI and ML can be trained to identify fraud. This is particularly useful in insurance and finance, where convolutional neural networks can be used in conjunction with document analysis to identify and flag likely fraudulent features, saving potentially millions of dollars a year otherwise lost to fraud.

Standardizing Document Processing and Storage

Manually sorting and storing documents opens up the possibility of irregularities, which reduces efficiency. Time must be taken to train employees in the correct business processes for handling documents and any mistakes or errors can lead to documents going missing. By automating this process as part of document analysis, the business procedures put in place are codified and automated, ensuring consistent document handling and storage every time.

Leveraging Patterns in Data to Develop Key Insights

AI and ML processes can be used across large data sets to discover key patterns and insights that are otherwise very difficult, or not possible, to discover when looking at documents individually. AI document analysis allows you to contextualize data that is spread across thousands to millions of documents and can help to evaluate market trends, such as seasonal variations in retail sales as an example.

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