Candidate Data Handling and Client Consent Gate (Onboarding)

Candidate Data Handling and Client Consent Gate (Onboarding)

1. 01

   Map every data field the hiring stack will touch before a single candidate record is imported

   List resume files, assessment scores, video interview recordings, and any AI-generated match ratings. Name the system of record for each field so nothing lives in two places.

2. 02

   Confirm the client's lawful basis for processing candidate data in writing

   For Canadian clients, Folksrh deployments typically require documented consent language tied to provincial privacy rules. Get the signed basis on file before sourcing begins.

3. 03

   Set retention windows per field and configure automatic deletion

   A one-way video screening clip and a resume rarely deserve the same shelf life. Assign a number of days to each field type and let the platform enforce it.

4. 04

   Decide which screening outputs a human reviews before any candidate sees an outcome

   AI matching in GoHire or resume scoring in Spark Hire can rank candidates fast, but a rejection that never passed a human desk is the fastest route to a client complaint.

5. 05

   Document the bias review cadence for any automated scoring model

   Pick a monthly or quarterly checkpoint, name who runs it, and record pass or fail against a defined threshold. An unexamined model is an unmanaged liability.

6. 06

   Write the candidate communication templates and lock the tone before launch

   Automated rejection and scheduling emails carry the client's brand. Draft them with the client, not for them, so personalization survives the automation.

7. 07

   Log the consent, retention, and review decisions in one client-facing document

   This becomes the reference when a candidate asks how their data was used, or when the client's legal team audits the retainer scope.