Introduction
GDPR compliance can be complex, particularly with maintaining accurate Records of Processing Activities (RoPA), conducting Data Protection Impact Assessments (DPIAs), and overseeing third-party processors as required under Articles 30, 35, and 28. Most privacy teams face bottlenecks in the data mapping process, which underpins all critical reporting activities under GDPR. Today, this process is highly manual, often relying on back-and-forth communication with application owners to complete surveys and spreadsheets documenting changes to data flows and sub-processors. This process must be repeated for every audit period or inquiry, and the challenge grows as the number of applications and development velocity increase. For instance, a company with thousands of code repositories may have a privacy team perpetually overwhelmed, struggling to keep up with code changes and reacting to third-party data violations and PII updates only after the data is in production.
This article will demonstrate how privacy teams can adopt a proactive approach to GDPR compliance that aligns with the speed of development, enabling full automation of compliance tasks such as data mapping, reporting, and detecting policy-based violations like PII oversharing with third-party integrations.
Keeping Track of PII – Simplifying Records of Processing Activities (GDPR Article 30)
Maintaining accurate Records of Processing Activities
GDPR Article 30 requires you to maintain detailed Records of Processing Activities (RoPA), covering how PII is collected, processed, and shared within your organization and with third parties. This includes specifying data categories, processing purposes, and external data transfers.
Maintaining up-to-date records is a significant challenge, especially as the number of applications and development speed grow. The data mapping process—fundamental to GDPR reporting—is largely manual and relies on frequent back-and-forth communication with application owners to complete surveys and spreadsheets documenting changes in data flows and sub-processors. The manual nature of this process, coupled with the complexity of data relationships that require ongoing validation, heightens the risk of errors and outdated documentation. This can result in non-compliance and challenging audit outcomes.
This workflow exemplifies the tedious steps required to track data flow changes for GDPR compliance.
How HoundDog.ai Helps
The HoundDog.ai Static Code Scanner runs as part of the CI pipeline, ensuring continuous mapping of PII data flows across all storage mediums and third-party integrations where it is exposed. With this approach, the HoundDog.ai Cloud Platform not only automates the data mapping process and the creation of Records of Processing Activities (RoPA) reports but also enables privacy teams to proactively address potential violations, such as oversharing PII data with third-party integrations that violate data processing agreements or introducing new types of PII without proper privacy reviews to ensure lawful processing. This approach eliminates the need for manual follow-ups while making compliance simpler and more accurate.
In addition to generating RoPA reports, the platform allows you to visualize how PII moves internally and through third-party connections, ensuring no flow is overlooked. Automated Data Flow Diagrams provide a clear view of how personal data is processed and shared across all storage mediums and third-party integrations, verifying compliance with Data Processing Agreements (DPAs).
Preventing compliance gaps with Proactive data flow tracking
Our platform’s proactive monitoring keeps your data flow maps current, reducing the need for manual reviews and complex data extraction efforts. It continuously tracks PII and updates your documentation to reflect changes before code is pushed to production. This helps you catch undocumented data flows or unexpected changes early, preventing them from becoming compliance issues during audits.
With a continuously updated PII inventory, reporting and audits become smoother and more straightforward. Having accurate, current records at all times means less scrambling when auditors request documentation, saving you time and reducing the risk of non-compliance. This visibility lets you maintain your RoPA efficiently and confidently, knowing you’re always audit-ready.
Handling Complex Risk Assessments – Automating Data Protection Impact Assessments (GDPR Article 35)
As GDPR Article 35 states, you need to conduct Data Protection Impact Assessments (DPIAs) when processing activities may pose a high risk to individuals’ rights and freedoms. These assessments help you find and address potential privacy risks.
Identifying these risks during development can be challenging, especially when PII is hidden in code, buried in logs, or passed through third-party APIs. DPIAs might miss important details without full visibility, leading to compliance issues and stress during audits.
How HoundDog.ai Helps
Using the HoundDog.ai Cloud Platform, you have a powerful way to maintain a detailed inventory of PII throughout your codebase. It tracks PII exposure within your source code, offering visibility into potential data handling risks without scanning unstructured data like logs, files, or APIs. This approach makes tracking risk identification and DPIA documentation far more efficient, reducing the need for time-consuming manual searches.
The platform’s automated updates keep your PII records current, aligning with GDPR Article 35 requirements. This means avoiding outdated or incomplete data when preparing for audits or providing DPIA documentation. Having up-to-date records saves time and provides confidence that your assessments are thorough and accurate.
Continuous PII monitoring helps you spot potential risks early in the development process. Our proactive tracking allows you to assess and manage these risks before code goes live, reducing the chance of costly post-production fixes. This ongoing visibility ensures that PII handling is always compliant and helps keep your DPIAs seamless in your workflow.
Integrating proactive monitoring into your processes makes audits less stressful, making compliance checks easier. You’ll be able to demonstrate that your organization meets GDPR standards and effectively protects personal data throughout its lifecycle.
Ensuring Third-Party Accountability – Strengthening Processor Oversight (GDPR Article 28)
GDPR Article 28 mandates you monitor your third-party processors and ensure they comply with their data protection obligations. This includes assessing their ability to meet GDPR standards and maintaining oversight of their data handling practices.
The challenge here comes when frequent third-party integrations occur during development, making it difficult to keep track of every interaction. This lack of visibility can lead to non-compliance and potential data mishandling, affecting your entire compliance strategy.
How HoundDog.ai Helps
Tracking third-party data flows can be complicated, but HoundDog.ai helps simplify this process by monitoring these interactions at the speed of development. The tool monitors data flows before code is pushed to production, identifying compliance risks and potential issues before they escalate. If any Data Processing Agreements (DPAs) violations are detected during development, the platform flags them, allowing your team to address concerns early on.
This proactive tracking means you don’t have to wait for audits or production to determine if PII data was overshared with third-party integrations. By keeping third-party interactions transparent and documented, you maintain better oversight and align with GDPR Article 28 requirements.
Avoid costly remediation by addressing issues pre-production
Catching potential non-compliance issues with third-party processors before the code goes live saves time and money. Our platform’s proactive monitoring helps you manage these risks during development, preventing costly fixes and last-minute adjustments later. Addressing problems before production keeps your operations smooth and helps during GDPR audits, making the process more efficient and less stressful.
Early identification of third-party risks helps you avoid costly remediation efforts and ensures that your data handling practices stay compliant. This proactive management keeps third-party oversight in check and reduces the chances of facing penalties or setbacks due to data mishandling.
Conclusion
We’ve covered the main challenges of GDPR compliance, including managing RoPA, DPIAs, and third-party oversight, and how HoundDog can help automate these tasks with proactive PII tracking and risk monitoring. Automating your compliance efforts saves time, reduces human error, and aligns your data protection practices with regulations. To simplify your GDPR compliance and minimize risk, book a call with HoundDog.ai and discover how we can help.
Here is an interactive demo of the automated RoPA creation workflow in the HoundDog.ai Cloud Platform.