Why check a CV for personal data
Recruitment agencies handle more personal data than almost any other small business. A single CV usually carries a name, a phone number, an email address and a home town; many add a full address, a date of birth, nationality, a photo or a driving licence number. Every one of those details travels with the CV when it is forwarded to a client, copied into an applicant tracking system or attached to an email. A quick audit before a CV leaves your desk tells you what you are about to share and whether your client actually needs it.
Data protection law in the UK and the EU is built on data minimisation: share only what the purpose needs. For most first-stage submissions, the client needs the career history, skills and qualifications, not the candidate’s home address or date of birth. Some details, such as health, religion or ethnic origin, are special category data and need even more care.
What the checker finds
- Names on the opening lines, repeated later in the text, typed by you, labelled (“Name:”) or listed under References.
- Email addresses and phone numbers in common UK, US and international formats, including numbers with country codes, brackets and spaces.
- Links and handles: web addresses, LinkedIn, GitHub and portfolio links and @handles that lead straight to the person.
- Postal addresses: street addresses, UK postcodes, US state and ZIP codes, Canadian postcodes and labelled addresses.
- Date of birth and age, which reveal age directly.
- Nationality, visa and right to work statements, which can reveal national origin.
- Other labelled details such as gender, marital status, religion, health, dependants and identity numbers.
Using positions to clean a CV quickly
Each identifier is listed with its line and column, counted from the top of the text. When you are editing the original Word file, that tells you exactly where to look, including in places people forget: a second phone number in the footer, a personal website in the skills section, a referee’s mobile number at the end. The highlighted view shows all of them in context, colour-coded by category.
What it cannot find
The checker matches patterns. It will not understand a sentence like “I moved to Manchester to care for my mother”, will not see text inside images or scanned pages, and cannot read hidden document properties such as the author or company fields of a Word file. It can also flag text that is not personal data, such as a product code shaped like a postcode. Treat the list as a strong first pass and read the CV yourself before sharing it.
Combinations identify people too
Removing every item on this list does not make a CV anonymous. A rare job title at a named employer, an award or a small university department can identify a person to anyone who knows the sector. If you run blind shortlists, also generalise employer names, institutions and exact dates for the stage where identity should stay hidden.
How your text is handled
Detection runs in your browser, so pasted text is never uploaded. A PDF or Word file you choose is sent once to our file reader to extract its text, processed in memory and discarded; it is not stored, logged or used for anything else. Our analytics count only that the checker was used.
Make privacy part of every submission
With CVPitch, each client template carries its own contact-removal policy. The approved CV exports as an editable DOCX and a matching PDF with the selected details removed, including from headers, footers and document metadata, while the original stays untouched. See pricing or try it free with 10 CVs.