The Pension Schemes Bill could expose a significant data gap across the UK pensions industry, as schemes struggle to meet the operational and technological demands of a more consolidated and sophisticated system, Finbourne chair, Toby Glaysher, has warned.

The adviser to the technology firm warned that while the bill represented a “welcome” step towards a more efficient and globally competitive pensions landscape, many schemes were not yet equipped to deliver on its ambitions.

“At a macro level, this is welcome legislation," he said.“If it achieves its goals of creating fewer, larger pension funds, delivering better returns for savers, and unlocking large pools of capital, that’s a win for members, sponsors and the UK economy.”

“However, I think we’re going to see a big hole. Data is both the challenge and the solution to most of what’s going on. Getting a single, accurate view of portfolios across multiple asset classes and data sources is extremely difficult.”

Glaysher argued that the issue was closely linked to the broader push for consolidation set out in the bill, noting that the success of reforms would depend on schemes reaching sufficient scale to build more sophisticated investment capabilities.

“The underlying issue is size,” he explained. “UK schemes haven’t had the scale required to build the level of sophistication seen in markets like Canada, Australia and the Netherlands, and as a result, much of the asset management has been outsourced.”

As consolidation gathers pace, particularly in the defined contribution and Local Government Pension Scheme space, Glaysher suggested this could enable schemes to internalise more investment expertise and increase allocations to private markets.

“In those leading markets, higher allocations to private assets came as a result of scale and expertise - not because of mandates,” he said, adding that proposed mandation powers in the bill were “unnecessary” and risked undermining trustee decision-making.

Meanwhile, the shift towards larger, more sophisticated schemes was also expected to change how portfolios are managed, with Glaysher pointing to growing interest in a total portfolio approach, which moves away from traditional strategic asset allocation models.

Rather than rebalancing portfolios to fixed allocations, this approach allows schemes to manage investments more dynamically across asset classes, but he stressed that it was heavily dependent on having the right data infrastructure in place.

“You can’t execute a total portfolio approach unless you have a total portfolio view," he said.

“Ideally, that view needs to be close to real-time, and many legacy systems simply can’t support that.”

Indeed, he warned that existing technology across the pensions industry was often ill-equipped to deal with the increasing complexity of modern investment strategies, particularly when it came to integrating public and private assets.

“Very few platforms can seamlessly combine public and private assets in a single view,” he said. “Legacy infrastructure just doesn’t lend itself to that level of integration.”

Given this, Glaysher urged schemes to prioritise investing in established technology solutions rather than building systems in-house.

“If you can buy it, buy it - don’t build it," he stated. "This is complex, and trying to develop it from scratch is both costly and risky.”

Alongside these operational challenges, he also raised concerns about whether trustee capability was keeping pace with the demands of a more complex pensions landscape, particularly as schemes took on greater responsibility for investment decisions.

“There is a shortage of trustees with deep knowledge of private markets and data,” he claimed, suggesting that this skills gap would need to be addressed as the industry evolves.

At the same time, he warned that the practical challenges of consolidation may be underestimated, particularly in administration and member records.

“Merging pension schemes is not straightforward," he warned. “Many legacy systems are still paper-based, and reconciling member data - especially where records are incomplete or outdated - requires significant manual effort.”

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