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  • 13 June 2021

How to digitize documents and classify data by using Artificial Intelligence

How to digitize documents and classify data by using Artificial Intelligence

How to digitize documents and classify data by using Artificial Intelligence 737 401 FinScience

written by Maurizio Crisanti

Digitizing a company’s documents brings many advantages. The conversion of documents into PDF files for archiving is a technology which has been used for years, but the new frontiers offered by Artificial Intelligence are now giving new life to archives, transforming them into data sources.

In every company, fiscal documents, contracts, correspondence, invoices and all the flow of documents concerning the type of business are filed. Document digitization is already commonly widespread, with the purpose of making physical spaces more efficient and allowing consultation on the basis of the parameters indicated, often manually, at the time of digital archiving of paper supports.

AI applied to document digitization 

Even in a process already adopted for years, digital evolution can bring innovation and new value. According to experts, AI is mainly a tool for automating repetitive tasks, processing large amounts of data to entrust a series of routine activities to specific platforms. In the workplace, document digitization with tools that use AI and Machine Learning algorithms helps simplify the most critical processes for the company.

In several contexts there are still large quantities of paper documents of great value that need to be converted into a digital form. Let’s think for instance about medical records, contracts, notary and law firm documents, tax documents and invoices or forms of all kinds.

What’s new is that we can now take advantage of platforms able to extract valuable data from scanned documents.

How does document digitization work?

The most used digitization process involves a kind of routine, which includes the following phases.

1) Scanning

This is the first step. After scannnig the paper documents with specific devices, now highly advanced – which also allow the scanning of bound volumes, automating the change of page – digital images are generated.

2) Optical Character Recognition

Optical Character Recognition, or OCR, is a method of converting a scanned image into text. Once the paper document has been digitized,  a specific software must convert it into text. By examining the lines and curves of the scan, the OCR consequently determines whether a combination is a particular sign or a letter of the alphabet, transforming the scan into a text file.

 3) File management

The management of digital files is generally carried out through a Document Management System platform, or DMS, which allows efficient management of digital documents by means of secure search and archiving functions, even in the cloud.

How AI and Machine Learning make the document digitization process more efficient

The adoption of Artificial Intelligence tools applied to document digitization brings in the following advantages:

Improved OCR functionality

Already in the processing phase with the OCR tool, Artificial Intelligence and the self-learning function applied to document digitization allow you to dynamically improve the software’s ability to transform images into correct text which fully corresponds to the original. It is common experience that traditional OCR software make mistakes in extracting text, due to the quality of the original document, the type of paper, the marks on the copy, the presence of lines or boxes. In the case of projects and blueprints or forms, for example, a normal OCR system cannot detect the position of the text, while a properly trained AI-driven OCR platform can do this.

Identification of the logical structure of a document thanks to AI

The identification of the logical structure of a document allows you to analyze thematically coherent titles, headings, sections and parts. This gives value to the texts, allowing the extraction of relevant information, indexing and automatic filing, with the ability to detect links between interconnected texts. Thanks to this, documents can be easily consulted once digitally archived, and this further reduces dependence on paper originals.

Automatic and consistent editing of digitized documents

Being able to automatically “read” information has another important use. Artificial intelligence algorithms can gather significant data and information by extracting it from documents. Companies are therefore able to extract specific datasets from their archives. It is possible to obtain information on how many documents have a specific feature, which documents concern a single customer or a single topic, and to extract statistics or generate invoices by using an automatic billing tool.

The advantages of digitizing documents by means of Artificial Intelligence platforms include the integration with business processes. Documents can be automatically sent to the employee or department for which they are intended on the basis of work routines based on simple rules. In this way, internal company document flows are automated.

There are many prospects for document digitization through AI. Of course, document dating is a constantly evolving science and it is necessary to use professionals to arrange an efficient system, able to speed up management, save time and money and allow the monetization of extracted data, when possible. FinScience with the Knowledge Discovery Machine solution, has gained experience in digital management of documents in several professional fields and can respond to the needs of digitization and enhancement of digitized documents.

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