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The need for privacy: Why some data must be kept private, and how Document AI can help

June 7, 2022

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Business documents, be it PDF files or emails, images or videos, carry crucial insights about the company, its operations, finances, clients, and even customer data. Data by itself is a treasure chest for businesses and cybercriminals. Many companies buy customer data to expand their market reach. And the same data is often leveraged by miscreants for unlawful practices. Imagine if your competitor lands up with your company’s confidential data? Or are criminals gaining access to your financial information? Data theft is a reality, and businesses are finding ways to use technology to protect their company and customer information.

This is where Document AI comes to the rescue. It uses NLP and ML technologies to help businesses unearth hidden value from bulk documents and ensures the data is secured and safe.

What is Document AI, and how does it help businesses?

Document AI is a solution powered by ML, NLP, OCR, Computer Vision, Sentiment Analysis, Text Processing, and other capabilities to process the colossal volume of documents and extract and digitize data faster and more efficiently than humans.

It is designed to broadly cover three basic requirements of businesses, such as:

Most enterprises still work with paper documents. Paper-intensive industries like insurance, banking, and healthcare often struggle to maintain a proper record of each document; hence, the data safety question remains largely unanswered. Such documents are easily lost or misplaced, along with all the crucial data they carry. But Document AI can save loss or misplaced data by digitizing documents and protecting them from such vulnerabilities.

A typical Document AI processing or intelligence platform does the following tasks:

AI document processing solutions like XtractEdge by EdgeVerve help scale and process millions of documents across the length and breadth of an enterprise, enabling faster and better decision-making.

Such an enterprise-ready platform enables:

How does Document AI keep business data private and secure?

In a world of increasing digital connectivity, businesses and customers leave behind digital footprints or crucial personal information. Once AI has structured that data, all that information is suddenly readily indexed. However, data in an unstructured format would be of lesser value, and finding anything specific amidst a colossal volume of data would be very much like finding a needle in a haystack.

The main risk lies in the fact that AI needs data to thrive. Without inputs, an AI-powered solution will not perform at all. And there lies the potential for data theft, which can cost millions of dollars in loss for businesses. If that data includes clients or customers’ personal information, then data theft can lead to legal actions against the company that suffered a data breach.

Machines can connect the dots and disclose sensitive data that they are not supposed to know. Differential privacy – where patterns of groups are revealed without sharing individuals’ information- – is the answer to this problem.

AI for documents can help deal with broader data privacy issues by training models to understand what information is and isn’t private, then redact resources proactively, depending on who’s accessing them at a given time. Document AI can edit critical information from text, images videos – think names, locations, license plate numbers, faces, and other personal identifiers. Also, certain information could be made available only to specific departments with permission from the user, for example. At the same time, business-sensitive data could be limited to those who have signed non-disclosure agreements.

In a nutshell, a Document AI solution like XtractEdge provides a robust framework helping businesses to process bulk documents at a go without the fear of losing crucial insights to outside parties. It ensures documents stay compliant with industry regulations and accelerates the extracting process to drive effective business outcomes with improved productivity.

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