The Pensions Regulator (TPR) has called on trustees to treat member data as their most important “strategic asset”, after its review revealed inconsistent approaches to data quality and warned that some schemes remain at risk of failing to meet their dashboards duties.

Publishing the findings of its engagement programme, alongside updated guidance on member data quality, TPR said that although dashboards preparation has driven “significant progress”, particularly on common data, some schemes have still not put in place the basic controls first set out by the regulator in 2010.

TPR stressed that high-quality member data is essential to ensure dashboards can function effectively and allow savers to locate all their pensions.

It warned that data quality failures could undermine member outcomes, noting that degraded or inaccurate information can lead to errors, delayed transactions, incorrect benefits, and costly remediation work for trustees.

This echoes previous warnings from the regulator on dashboards' readiness, in which it suggests that 'data debt’ could threaten scheme's being prepared ahead of the deadline, urging trustees and administrators to work together to deliver even higher standards of administration and help achieve better outcomes for savers

TPR's latest engagement exercise, which ran from October 2024 to September 2025, covered schemes of all sizes but focused particularly on those with more than 1,000 members.

It was designed to challenge schemes that may not meet the regulator's expectations and to help ensure they could comply with their dashboards duties.

TPR found that although most schemes could provide data scores when requested, for some, engagement served as the prompt to measure their data for the first time.

Others delayed submitting scores because they were midway through data cleansing linked to buy-out activity or transitioning to a new administrator.

The regulator emphasised that its General Code requires trustees to assess the need for a data review exercise at least annually, as member data “degrades and changes” over time.

The initiative also revealed that trustees’ approaches to scheme-specific data were highly variable, despite TPR’s expectations that this should include all data needed to calculate benefits, process member events and queries, and reflect scheme features such as contracting-out or remediation exercises.

Indeed, while almost all schemes used TPR’s definitions for common data, scheme-specific items were inconsistently identified and measured across the schemes engaged.

The format and content of data assessment reports also varied widely.

Some lacked detail on the testing methodology, which TPR said can inhibit trustees’ understanding and limit their ability to scrutinise administrator work.

The regulator noted examples of good practice in which administrators provided clear explanations, contextual information, and recommended actions, but also said that trustees often relied too heavily on administrators.

Meanwhile, TPR said it observed widespread data cleansing activity and found that many improvement plans were informal, fragmented, or vague, with some schemes citing only loose timeframes, such as “by Q2 2026”.

It added that few provided standalone improvement plans that set out objectives, timelines, resource requirements, responsibilities, and dependencies.

Subsequently, the regulator emphasised that trustees should ensure that improvement actions are prioritised appropriately and that plans reflect all data needed for both dashboards matching and dashboards value calculations, as value data will form a central part of its next phase of engagement.

TPR executive director of market oversight, Julian Lyne, stressed that good data is the "foundation of good governance and a trustee’s most important strategic asset. "

"Trustees are accountable for ensuring member data is correct - no one else," he continued.

"Maintaining its quality is an ongoing responsibility, because neglect can be costly and have real-world consequences for savers."

Alongside the report, TPR published updated scheme member data quality guidance, replacing its previous record-keeping guidance.

The new document reinforces that trustees are legally accountable for the quality of member data and must ensure strong governance and internal controls even where duties are delegated to administrators or sub-committees.

Indeed, the guidance describes member data as a “strategic asset” essential for paying the right benefits at the right time, supporting accurate defined benefit (DB) funding plans and timely defined contribution (DC) core transactions.

It also stressed this includes meeting regulatory requirements, improving accessibility and inclusivity through digital tools, and enabling schemes to achieve long-term objectives such as buy-out or consolidation.

Furthermore, TPR warned that governing bodies should ensure administrators have adequate controls, obtain regular data reports, consider data quality at board meetings, maintain appropriate entries in the risk register, allocate sufficient resources to address issues, and ensure all data is processed in line with data protection legislation and ICO guidance.

It also suggested that larger schemes may consider establishing dedicated data quality teams or sub-committees.

The regulator confirmed that the next phase of its data-quality programme began in July this year, through a deep dive into the dashboards preparations of the UK’s largest schemes, with further work covering the wider dashboards-in-scope universe to begin in 2026.

TPR concluded that managing data quality “is not a one-off exercise”, urging trustees to build on the momentum created by dashboards and ensure data remains accurate, complete and reliable on an ongoing basis.

“With the pensions dashboard deadline less than a year away, the need for reliable data has never been more urgent," Lyne warned.

"The gaps identified in our report risk undermining dashboard readiness and highlight the importance of trustees adopting robust, consistent practices across all aspects of data management.

"Good data must be complete, accurate, timely, consistent, unique, valid and properly managed,” he added.

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