End-to-end privacy management refers to the process of protecting sensitive data throughout its entire lifecycle, from the moment it is collected to the point where it is destroyed. This approach involves implementing a comprehensive privacy management program that includes privacy policies, procedures, and controls designed to safeguard data and protect individual privacy rights.
Developing or acquiring solid expertise in privacy laws and regulations and industry best practices is necessary to determine what is required from organizations collecting, using, and disclosing personal information. Many of the controls can then be automated, and we will address how Private AI, in particular, can help with that.
From Collection to Destruction
End-to-end privacy management is critical in organizations handling large amounts of sensitive information that are regularly targeted by cybercriminals. Financial institutions and custodians of healthcare information must be especially careful. Here is a brief overview of how end-to-end privacy management works:
Data Collection: Many institutions collect a variety of personal information from their customers, such as names, addresses, social security numbers, employment history, health data, income, or bank account information. End-to-end privacy management begins with the collection of this data, which should be done in a secure and transparent manner. The collection of personal data generally requires a legal basis, which is often consent. In order for consent to be valid, privacy laws require that organizations disclose how they are handling the personal information they are collecting.
Data Use: Organizations of course use data for a variety of purposes, such as research, account management, or marketing. Often, several different uses are made of the personal information they collect. End-to-end privacy management requires that these uses are limited to the purposes for which the data was collected and that customers are informed of how their data are being used at the time of collection, or before the personal information is put to a different use than was originally disclosed.
Data Processing: Once data are collected, it is processed and stored in databases and other systems. During this stage, end-to-end privacy management involves implementing strong access controls, encryption or anonymization, and other security measures to protect the data from unauthorized access, modification, or deletion. It is advisable to set up your systems with privacy considerations in mind (privacy by design) as it is much harder to fix things later. Technical issues aside, business considerations will get in the way and other projects take priority. This can mean exposure to significant compliance costs.
Data Sharing: Many organizations may need to share customer data with third parties, such as credit reporting agencies, payment processors, research institutions, healthcare service providers, or the public. Data sharing increases the risk of data breaches and privacy violations, so it is essential to implement strong data protection and security controls when sharing data with third parties. In the sharing stage, end-to-end privacy management involves first a thorough assessment of the third party’s privacy posture. This needs to occur before entering into a business relationship. Your findings may mean that the third party poses an unjustifiable threat to the privacy of the data and hence your business. The next step is to implement strong data sharing agreements, including data protection and security controls, to ensure that third parties handle data in a manner that is consistent with the organization’s privacy policies and applicable laws and regulations.
Data Destruction: Finally, when customer data are no longer needed, it must be securely destroyed. End-to-end privacy management involves implementing secure data destruction processes, including the use of data wiping or shredding software, to ensure that data are completely and irretrievably destroyed. Privacy laws often allow data anonymization as an alternative to the disposition. This can enable organizations to effectively use the data for research and analytic purposes.
Technical Solution
The ISO standard on privacy by design mentions “de-identification or anonymization tools, up-to-date PII inventory, [and] consumer PII locator” among the technological solutions that keep personal information safe and can thus satisfy one of the privacy by design requirements. Private AI can help with exactly that. Private AI can be easily deployed within your environment to scan 9+ file formats for 50+ types of PII across 47 different languages. The user can then generate a report showing the types, locations, and quantities of personal information found, which can be shared with the organization’s CISO, CPO, CDO, or with auditors and be used to improve your organization’s overall security posture.
Try our web demo to see our de-identification tool in action, or request an API key to try it yourself on your own data.
