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Creating a Comprehensive View of Privacy Risk: Third Party Risk Strategies for SRM Leaders

There’s a lot of value to working with third parties. You can gain access to specialized skills, and it’s often more cost-effective for your organization than building your own in-house tools or capabilities. However, working with third parties also brings a sizable amount of privacy risk. 


Until recently, companies working with third parties were mostly concerned about exposure to security risks. They take a great deal of care to protect themselves against the increased vulnerability to data breaches, ransomware, and malware that comes along with working with third party organizations. 


Third-party data privacy risks are real

But data privacy risks are equally important. Third parties frequently need access to user and customer data, sometimes quite sensitive data and in considerable volume. Naturally, the more entities have access to a given set of data, the greater the risk of a data breach or successful hacking attempt. Given that 82% of companies have given third parties vendors highly privileged roles, and 98% of businesses work with at least one third party that’s already experienced a data breach, it’s not surprising that third party data breaches are so frequent.


International data regulations are mushrooming, raising the risk of fines if you don’t have sufficient data protections in place. A data privacy breach can be just as embarrassing as a data security breach, and damage your reputation and trust to just as great an extent. Consumers are increasingly worried about data privacy, and prefer to buy from businesses that promise to protect their data, which means that your business partners will prioritize companies with robust data privacy policies. Data is “the new oil,” so if you lose access to data, your business could suffer significantly. 


In response, there’s a growing realization about the need for organizations to protect themselves against data privacy risks in general, and in their relationships with third parties in particular. More than half of major organizations are looking for new tech solutions to help them manage third-party data privacy risks, but tech can only go so far. Organizations also need effective security and risk management (SRM) practices in place. It’s been found that companies with the loosest privacy policies are almost twice as likely to suffer a data breach than those with the strictest, and lose seven times as much data when a breach does happen. 


Top 5 actions to smash data privacy risks

Here are 5 things that companies should address in order to manage data privacy risks in their third party relationships. 


1. Establish primary ownership

Clarifying who is the primary owner of the data is a vital foundation for data privacy. It solidifies lines of authority, decision-making, and accountability for data-related activities, which then makes it possible to set roles and responsibilities around data management. 


In the event of a data breach or privacy incident, identifying the primary data owner is critical for prompt and effective incident response. The owner can take the lead in coordinating the response efforts, notifying affected individuals, and complying with legal and regulatory obligations. 


The main way to make sure that everyone knows who the primary owner is through a data protection agreement (DPA) between your company and each third party. 


2. Sign a data processing agreement 

A DPA (data processing agreement) is a legal document that obligates third parties to a certain level of data protection. It constitutes an agreement about what the third party can and cannot do with the data. There are many templates online, like this one


Besides establishing ownership, a DPA is vital for protecting you from liability if a breach occurs due to the third party’s negligence. Without one, you will be held accountable for not having sufficiently safeguarded the data you collect. 


A DPA covers these critical issues:

  • Which third party services may access data
  • When, why, and how data may be transferred between territories 
  • Which types of personal data are collected and shared
  • How to respect data subject rights, such as the right to access, change, or restrict processing for their data, and the right to be informed of a data breach
  • Procedures for deleting or returning personal data to the company 
  • Your access to the third party’s systems to audit data and data management


3. Ensure a comprehensive view of data privacy risks


You can’t set up robust data protection policies or complete a reliable DPA unless you completely understand all the risks that you face. This means carrying out a deep dive into all the roles and responsibilities for data use, storage, transfer, and more, in every third party system, as well as clear escalation criteria for decision makers.



You need to discover information like:

  • Which types of data are being stored by the third party
  • Which systems and applications are used to process the data
  • The potential impact of a data breach


Current best practice calls for organizations to manually complete a questionnaire for each third party, a manual process that includes interviewing engineers about their code, waiting for a code review, and often returning to ask more questions. However there are new, automated ways to complete this process, for example with Privya. 

Privacy Risk - Privya AI


4. Set up ongoing monitoring 

Once you find out about a third party’s data use, storage, and sharing practices, establish primary ownership, and sign a DPA, you need to put into place procedures that allow you to monitor third party data use in a continuous manner. This includes educating all relevant decision-makers about data privacy risks. 


Elements to monitor include: 

  • Changes to the scope or purpose of the third party’s data usage
  • Changes to their data protection strategy
  • Changes to key personnel who have access to data


5. Implement automation 

Manual data protection and privacy processes are prone to error, slow, and unreliable. They simply cannot keep up with the pace of data processing and sharing today. Data processing and analytics is mostly automated, to take advantage of advanced artificial intelligence (AI) and machine learning (ML)-powered analytics. 


Data privacy risk management needs to apply the same level of automation. Tasks like gathering information about the third party’s data usage and monitoring practices to identify patterns that could indicate a security risk are just two examples that benefit from automation. 


Accountability is a major hurdle for third party data management

The concept of accountability is significant for both security and privacy in the business world, and one of the key principles of GDPR. Accountability means that your organization needs to show that it’s taken all the reasonable measures possible to protect itself and its users, partners, and data subjects. 


When it comes to security, it’s relatively easy to demonstrate accountability. Businesses that undertake specific security measures, like implementing access permission controls or multi-factor authentication, can expect to have met accountability requirements. 


But accountability for data privacy is more nebulous. There are no fixed actions that organizations can take to prove they have anticipated all reasonable risks, and that a given data breach or issue that arises during an audit was not due to negligence or carelessness. 


However, most data privacy experts agree that as long as you have taken enough robust measures, you can claim to have done your best to protect your data and are not accountable for whatever took place. Using advanced data privacy automation can be an effective way to prove that you’ve gone beyond basic data protection and have done something more meaningful to prevent a data breach. 


Privya strengthens your third party data privacy risk profile 


Privya uses AI to automate code-mapping and scanning, delivering automation solutions for third party data privacy assessments. Privya can instantly detect the presence of any third parties in your code, and reveal the purpose, context, entity, and the type of data being used in any instance. 


Without Privya, as mentioned above, organizations need to interview engineers, wait for them to manually carry out a code review and report back to you, and then complete a questionnaire. Since developers are continually writing and editing code, the report  – besides being time consuming to create – is just a snapshot in time, already out of date by the time you receive it. It’s a never-ending chase to update data usage and storage reports before they become obsolete. 


But with Privya, all these tasks are carried out automatically. Privya helps you complete third-party data privacy questionnaires in the most accurate way possible. Code reports are refreshed in real time, so there’s no need to worry that your DPA is based on out-of-date information. Privya also makes it possible to monitor third parties for changes to their data usage, so you won’t be caught unprepared. Privya can deliver alerts whenever something changes. 

Using Privya can be an excellent way to demonstrate accountability and prove that you have done more than could be expected to protect against a data breach. 



Don’t let your third party relationships weaken your data privacy profile


Organizations that handle sensitive data together with third parties must prioritize strong security measures and risk management strategies. By incorporating automation into the process of identifying potential risks, developing a holistic understanding of privacy risks, and establishing continuous monitoring, leaders in security and risk management can proactively safeguard their data and assets from potential threats that may arise from third party relationships.


Learn more about Privya today.

Uzy Hadad
Uzy Hadad


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