Data subject requests (DSRs) refer to the right of individuals to access their personal data held by an organization. It is a fundamental right enshrined in the General Data Protection Regulation (GDPR) and other privacy regulations. Organizations have to handle these requests within a specific time frame, usually one month, and provide the data in a structured and commonly used format.
Given the increasing volume of DSRs, automating the process can significantly improve efficiency, reduce costs, and ensure compliance with regulations. Automating the DSR process involves three main steps: identifying the request, verifying the requester’s identity, and processing the request. Let’s look at each step in more detail. If this information is insufficient, we recommend checking Ethyca’s article on DSARs.
Step 1: Identifying the Request
The first step in automating the DSR process is to identify when a request is made. This can be challenging as DSRs can come in various forms, such as emails, phone calls, or online forms. Moreover, the request may not explicitly state that it is a DSR. For instance, an email that says, “Can you please send me all the information you have about me?” could be a DSR.
One way to address this challenge is to use natural language processing (NLP) to extract DSR-related keywords and phrases from incoming messages. For instance, an NLP algorithm can scan incoming emails for phrases like “data protection,” “access request,” or “right to be forgotten.” If such phrases are identified, the message can be flagged as a potential DSR, and the next step of the process can be initiated.
Step 2: Verifying the Requester’s Identity
Once a potential DSR is identified, the next step is to verify the requester’s identity. This is crucial to ensure that the organization does not inadvertently disclose personal data to the wrong person. Verifying the identity can be done through various means, such as asking for a government-issued ID, a password, or a security question.
To automate this step, organizations can use identity verification software that checks the requester’s identity against multiple sources, such as public records, credit reports, or social media profiles. The software can also use facial recognition technology or voice biometrics to verify the requester’s identity. Once the requester’s identity is verified, the organization can proceed to the next step.
Step 3: Processing the Request
The final step in automating the DSR process is to process the request. This involves locating and retrieving the requested personal data, reviewing it for accuracy and completeness, and providing it to the requester in a structured and commonly used format. The organization also has to ensure that any sensitive or confidential information is redacted or removed.
To automate this step, organizations can use data discovery and management tools that can search through various data sources, such as databases, emails, and files, to locate the requested data. The tools can also categorize the data based on its sensitivity or confidentiality and redact or remove any sensitive information automatically.
Moreover, organizations can use workflow automation software to track the progress of the DSR, assign tasks to relevant personnel, and ensure that the request is handled within the stipulated time frame. The software can also generate automated responses to the requester, informing them of the status of their request and providing them with a link to download the requested data.
Conclusion
In conclusion, automating the DSR process can significantly improve efficiency, reduce costs, and ensure compliance with regulations. By leveraging technologies such as NLP, identity verification software, data discovery and management tools, and workflow automation software, organizations can streamline the DSR process from identification to processing. Automating the DSR process not only benefits organizations but also enhances the privacy rights of individuals by ensuring timely and accurate access to their personal data. As the volume of DSRs continues to grow, automating the process is becoming increasingly essential for organizations to stay compliant and meet their obligations under privacy regulations.