Data privacy is a major concern for both organisations and individuals. Regulations like GDPR hold organisations more accountable for protecting personal data.
Given that data subject access requests (DSARs) need to be actioned within 30 days (unless an extension is sought), many businesses now find themselves struggling to manage the volume and complexity of these requests and often find themselves under pressure to find, identify and redact personal information within the allotted time. Its not just the time that these requests but also the costs of them too, findings from The Data Privacy Group show that these requests are costing businesses between £72,000 and £336,000 a year, with Gartner estimating a single request can cost around £1000. This is where Microsoft Priva can be used to help save you time and effort, reducing those costs.
Priva Subject Rights Requests is a comprehensive data privacy management solution designed to simplify and automate the processing of data subject requests. Utilising advanced AI-driven capabilities, Priva helps organisations efficiently locate and redact personal data, ensuring timely and accurate responses. Some of the things that it can help with are:
Managing Data Subject Requests at Scale
Priva Subject Rights Requests enables organisations to handle large volumes of data subject access requests efficiently. This is particularly important for companies with extensive customer bases, or those operating in multiple jurisdictions. By automating the quest management process, Priva ensures that each request is tracked, processed and responded to within the required timeframes, reducing the administrative burden on staff.
Discover Personal Data Across Multi-Cloud Estates
In today's digital landscape, personal data is often spread across various cloud platforms and storage solutions. Priva helps organisations discover and consolidate this data, regardless of where it resides. This capability is crucial for providing comprehensive responses to DSARs, as it ensures that no piece of personal data is overlooked.
AI-Driven Data Identification and Redaction
Priva leverages advanced AI to automatically identify and redact sensitive information in documents. This process involves scanning documents for personal data such as names, addresses, and financials, and obscuring it to protect privacy. By using AI, Priva reduces the likelihood of human error, ensuring that all sensitive information is accurately identified and reacted, thus maintaining compliance with data protection regulations.
Regulatory Compliance
Priva's robust compliance features are designed to help organisations meet various regulatory requirements, such as the GDPR, CCPA, and other data protection laws. These features include automated audit trails, compliance reporting, and real-time monitoring of data processing activities. By ensuring that all DSARs are handled in accordance with legal requirements, Priva helps organisations avoid potential fines and penalties.
Cost Savings
By streamlining the DSAR process, Priva reduces the need for manual data handling and the associated costs. Automation minimises the time and resources required to process each request, allowing staff to focus on more strategic tasks. This efficiency translates into significant cost savings for organisations, particularly those dealing with high volumes of DSARs.
Increased Trust
Demonstrating a commitment to data privacy and providing timely responses to DSARs fosters trust and confidence among customers and stakeholders. When individuals see that an organisation takes their privacy seriously and responds promptly to their requests, they are more likely to trust that organisation with their personal data. This increased trust can lead to stronger customer relationships and positive reputation in the market.
How Perspicuity Can Help
We can help you manage your Data Subject Request Process whether you want to learn how to use Priva Subject Rights request, or just need help building a more streamlined DSAR practice to save you time using other tools from the M365 stack.