Cracking the code on pay gaps: Privacy-Preserving tech helps drive fair pay in the EU

But while the directive is rooted in fairness, its implementation raises complex questions: especially around how to handle sensitive salary data responsibly.

The EU Pay Transparency Directive is a bold legislative step. It requires companies with more than 100 employees to report on gender pay gaps and disclose how salaries are determined, putting compensation under a spotlight that many businesses have never experienced. The aim is simple: expose unjustified differences in pay and empower employees to challenge them.

But this increased transparency also introduces new layers of responsibility. Employers must now navigate the tightrope between transparency and confidentiality. How can they openly assess and address inequalities without compromising the privacy of individual employees?

While the directive is, at its core, a compliance requirement, it also offers a rare opportunity for organizations to evaluate their internal practices and reflect on the fairness of their compensation strategies. It’s a chance to move past outdated assumptions, unintentional biases, and opaque pay structures, towards something more equitable and accountable.

The directive’s success hinges on accurate, large-scale analysis of pay data. But salary information is among the most sensitive data a company holds. Conducting the kind of deep analysis needed to uncover systemic issues - across gender, ethnicity, department, and seniority - while remaining compliant with GDPR and earning employees’ trust is no easy task.

This is where secure, privacy-preserving technologies come into play.

Multi-Party Computation (MPC), long considered a theoretical concept, was always driven by real-world applicability. While initially developed in academic circles, its practical potential is now becoming a reality, enabling organizations to analyze encrypted data and extract insights without exposing sensitive information.

In real terms, MPC means companies can answer questions like: “Are women being paid less than men in equivalent roles?” or “Does a racial pay gap exist in leadership positions?” 

All without revealing a single individual’s salary.

This approach mirrors findings from research at Boston University, where data science methods helped uncover hidden compensation disparities that were not visible through surface-level metrics. With MPC, businesses can now apply those same advanced techniques internally, without the associated privacy risks.

As highlighted in Azets’ breakdown of the directive, organizations that embrace transparency early will not only ensure compliance but gain strategic advantages, from improved talent retention to enhanced brand trust. But as mentioned in the article, transparency needs infrastructure. And for many companies, that means finding tools that can handle sensitive data with precision and care.

This is where Partisia comes in. As a pioneer in secure Multi-Party Computation, Partisia offers advanced MPC-based solutions that enable companies to analyze salary data across demographics, without ever exposing individual pay details. Their privacy-first approach helps businesses fulfill the technical and ethical demands of the Pay Transparency Directive.

By empowering HR teams and leadership to uncover wage gaps securely and accurately, Partisia helps organizations not just check compliance boxes - but take meaningful steps toward pay equity. With MPC at its core, Partisia’s platform builds trust, preserves confidentiality, and supports a culture of accountability and fairness.

In a time when transparency and data protection must go hand in hand, Partisia.com is helping organizations meet the moment - delivering clarity without compromise.