Learn how new personal data safety policies are challenging businesses, and what AI can do to help process the information. (10 minutes reading)
What exactly is the GDPR?
With the incredibly massive flow of information related to people and businesses circulating through the web, there is more concern for privacy and personal data than ever before. For this reason, many governments set out to establish regulations and other forms of protection to safeguard citizens and offer an additional layer of data protection.
In Europe, for instance, the General Data Protection Regulation (also simply known as “GDPR”) was instituted as an effort to standardized data protection for all individuals residing within the countries of the European Union. The GDPR also relates to the circulation of information and personal data outside the European Union.
The purpose of the GDPR is, ultimately, to simplify international regulations and achieve a “common ground” that will allow for unified safety procedures in relation to personal information.
In layman terms, the GDPR allows personal data protection to be processed the same way across different EU countries and outside the EU, in order to offer the same standards of privacy protection enforcement.
The idea of unifying data safety standards is often referred to as “harmonization,” meaning that the GDPR aims to create uniform regulations across the European Union, making for a more efficient and predictable environment through the 28 countries that are currently members of the EU.
The GDPR is the “new kid on the block” in terms of regulation, as it will be finally enforced from May 25th, 2018. The new rules will effectively replace data protection policies that have been in effect since the early 90s. As you might guess, the old directives might not be the best solution to cater to the incredibly large data traffic of the contemporary world. The GDPR is indeed a much-needed update on a code that’s now over twenty years old.
Having said that, organizations are still going to be required to be prepared by the time the new regulations come into effect. The time to get started is now. Read on to learn more about what you can do to get ready and how new technologies can help you save time while implementing the effectiveness of your data analysis and achieve GDPR compliance according to the latest requirements.
Why is it important for businesses to keep track of their sensitive data?
Even before the advent of the GDPR, keeping track of sensitive data has often been a huge priority for businesses. Misuse or mismanagement of personal information can lead to many unpleasant consequences, including costly lawsuits, penalties and other issues that might disrupt the productivity or the reputation of an organization. For this reason, many companies go to great lengths to secure fast, efficient and reliable data management solutions to comply with the highest data safety standards possible.
The new changes brought on by the General Data Protection Regulation will not only affect the countries of the European Union. They will undoubtedly generate a ripple effect on a global basis.
At this time, many companies all around the world are assessing their situation and making sure they can drive GDPR compliance.
The General Data Protection Regulation is, in fact, applicable in each EU country, with the purpose to unify data protection standards. There are many companies out there who already hold excellent privacy standards that are attuned to the new guidelines, but not everyone is already prepared.
In case of failure to comply with the new GDPR standards, companies can risk huge fines and costly penalties starting from May 2018, when the GDPR will officially be enforced.
How will the GDPR affect businesses and organization?
The GDPR is poised to make a huge impact regarding data security worldwide, particularly improving information safety, breach notification standards and other key factors related to modern ethical standards. In particular, new GDPR guidelines offer a more accurate definition of “personal data” herein intended as “any information relating to an identified or identifiable natural person (data subject).
By shedding more light on the very definition of personal data under the GDPR rules, it is also easier to enforce regulations and determine security breaches, whether they were merely accidental or conscious unlawful attempts to take advantage of private information without disclosure or permission. Such guidelines can help reduce the risk of issues such as fraud and identity theft, among others.
As with most changes and new policies, the GDPR could present some challenges to companies, as they will need to embrace these new standards.
The new regulations affect some of the most important aspects of the workflow of many businesses, especially managing sensitive personal data.
In an effort to adapt to the new policies, businesses need to rethink their strategies and come up with new, effective solutions to track their data and archive them as seamlessly as possible, either as digital files (such as .PDF) or on actual paper. It’s important to understand that archiving information and changing data tracking operations might be a monumental task for a large organization, who might be accustomed to dealing with millions upon millions of data entries.
Can Robots help businesses comply with the newly established GDPR standards?
Sensitive information, such as personal data, is found in documents very often, both in digital and paper form. For this reason, companies are required to analyze their available data in minute detail.
Think of a huge corporation with decades of customer information stored in their database, or a governmental historical archive, just to give you a couple of examples. In both cases, we are essentially talking about significant amounts of data, requiring complicated, labor-intensive efforts to be properly accounted for.
The new GDPR guidelines require all sensitive data to be properly tracked and protected. As you might guess, this might require a lot of work and human resources.
some cases, tracking and identify all relevant information manually might simply not be an option, and even when more sophisticated archiving tools are available, the workflow might simply be enormous and time-consuming.
This is where robots come in handy. In recent years, artificial intelligence set out to become one of the most exciting new trends in the world of business. Sophisticated AI solutions, often dubbed “robots” have been successfully implemented in different areas, ranging from intelligent customer service applications to data management and information archives.
A sophisticated AI algorithm could certainly come in handy when it comes to tracking data to account for GDPR criteria.
Analyzing millions of document is a piece of cake for a robot: AI can indeed help organizations save massive amounts of money, time and resources. Solutions such as Doc Digitalizer are particularly perfect for this particular purposes. Robots can easily handle, classify and interpret documents with the aim to identify vital information from large bulks of content.
By understanding the nature of the documents, AI solutions can effectively categorize each file and determine whether or not each document features sensate data under GDPR regulations. Establishing automated data processing processes such as the ones described earlier is particularly important for businesses, particularly when they need to account for a very large volume of data. AI solutions can help businesses apply the same processing intelligently and reliably to a massive amount of files, without the need of constant human supervision.
Doc Digitalizer is a great example of how this works. This intelligent application with the ability to analyze and catalog documents, allowing for organizations to establish new automated processes.
This state-of-the-art data management solution comes in handy for organizations looking to comply with GDPR guidelines and be prepared for this challenging switch to new regulations in the best possible way.
The team at Doc Digitalizer set out to create an intelligent solution that “learns” how to read documents and classify them properly, without the need for consistent human efforts, thus minimizing labor and maximizing efficiency to the new standards expected from the GDPR starting this spring.