Adaface GDPR FAQs
Adaface is committed to adhering to the General Data Protection Regulation (GDPR) policies. The following are some of the frequently asked questions to help our clients and candidates.
Clients/ Organizations/ Users with an Adaface account
What data do we collect?
When a candidate begins an assessment session initiated by an Adaface client, we store the following information of the candidate on behalf of our client:
- Email address
- Optional at the client's discretion: Phone number, The last school attended, academic degree, major, programming experience, resume, and a link to social profiles (GitHub, LinkedIn, etc).
- Metadata collected for proctoring: IP Address, Webcam snapshots, Browser usage data and Session recording data. Some of these data points are optional and collected at client's discretion.
If the recruiter uses an Adaface account for inviting candidates to assessments, we store the following information:
- Email address
- Phone number (Optional)
Who is responsible for candidate data?
Any Adaface client that administers the assessment owns the data of all candidates that took the assessment. The responsibility of updating and deleting all candidate data when requested by a candidate lies with the client. Adaface provides our clients with necessary support (customer support/ product features) to carry out any such requests however the company wants to.
For how long is the candidate data stored?
It depends on the contract with our client. By default, we store data until it's explicitly removed. But we provide provisions to set up a periodic data removal process for our clients on a contract-to-contract basis. However, we always support data deletion through requests sent to [email protected] for all of our clients. We delete data at the specified/ requested time by our clients with an additional grace period.
Who has access to candidate data?
- Clients that administer the assessment.
- Candidate through requests to Client.
- Adaface internal team only when a support request is raised by the Client and data access is necessary to support such request.
Which roles/ permissions are required for employees of the client to have access to candidate data?
All users of a client account with roles - Candidates Admin, Tests Admin, Super Admin have access to candidate reports.
How do clients request candidate data to be deleted?
For enterprise users with specific contracts, they can delete the candidate entry using 'delete' action in candidates' view. Furthermore, you can email us at [email protected] with the list of candidates' data to be deleted. You can also contact your Adaface Customer Success Manager for such requests.
How to access audit logs?
Adaface maintains logs of all actions that are state changing as well as unpermissioned actions for troubleshooting and security. Super Admins of a client account can view the audit logs from their dashboard. Any further processing requests of audit logs should be routed through [email protected] or your Adaface Customer Success Manager.
Can the deleted data be reinstated?
Can we edit a candidate's data?
For editing a candidate's data, please contact us at [email protected] with details about the request.
Candidates who took the Adaface technical chat
Can I delete/ edit/ view/ access my test attempt or personal information?
Adaface is an assessment provider and the data of the technical chat including the scorecard is owned by our client who administered the assessment. Please contact the client who administered the assessment directly to request the deletion of your data. If you require any help in making such requests, you can contact us at [email protected]
Industry-accepted best practices and frameworks
Our security approach focuses on security governance, risk management and compliance. This includes encryption at rest and in transit, network security and server hardening, administrative access control, system monitoring, logging and alerting, and more.
We evaluated several of their competitors and found Adaface to be the most compelling. Great default library of questions that are designed to test for fit rather than memorization of algorithms.