Why Complex Groups Need Group Relief Optimisation

In the UK, group relief allows a company to surrender its tax losses to another company in the same corporate group. On the surface, this mechanism seems straightforward: match losses with profits and reduce the group's overall corporate tax liability.

But when it comes to complex groups, those with many entities, non-coterminous accounting periods, and frequent changes to group composition, the reality is far more intricate. In these cases, optimising group relief becomes essential to avoid leaving tax savings on the table.

The UK isn't alone. Similar mechanisms exist in other jurisdictions such as Cyprus, Ireland, New Zealand (group loss offsets), Norway (konsernbidrag), Singapore, and Sweden (koncernbidrag), though the specific rules and opportunities vary by country.

Complexity isn't just a detail—It's the Challenge!

A "complex group" might include any of the following characteristics:

• Multiple loss-makers and profit-makers
• Subsidiaries with different accounting year ends (non-coterminous accounting periods)
• Entities that joined or left the group during the year
• Interactions with carried-forward or carried-back losses
• The loss restriction
• The corporate interest restriction
• Group members with double taxation relief or other tax adjustments

Each of these factors adds a layer of decision-making to the group relief process. Suddenly, it's not just about whether losses can be surrendered, but how much, to whom, and when they should be surrendered for maximum impact. When accounting periods don't align, group relief becomes a strategic lever, and optimising it becomes essential to avoid leaving tax savings on the table.

The risk of manual allocation

Despite the complexity, many companies still approach group relief manually, relying on spreadsheets or tax software that simply report the maximum surrenderable amounts available. While this may suffice for straightforward cases, it quickly becomes inefficient when the group structure is more involved.

Moreover, blindly applying the maximum surrenderable amount isn't always optimal. In many cases, a partial surrender can help make more efficient claims later in the sequence. For example, by strategically applying partial surrenders, groups may significantly reduce taxable profits over an approach that simply applies the maximum surrenderable amount each time. This is illustrated in the example described here.

Optimisation: From compliance to strategic advantage

This is where group relief optimisation becomes critical. By applying advanced algorithms to evaluate the full set of possible surrender combinations, within the constraints of the legislation, it's possible to:

• Maximise tax savings by identifying the most efficient use of losses across multiple scenarios.
• Ensure compliance with group relief rules, particularly sections 138–142 of CTA 2010 in the UK.
• Save time and reduce risk by automating what would otherwise be a complex, manual process requiring significant senior tax professional time.

For large groups, this turns group relief from a routine compliance exercise into a powerful lever for managing corporate tax liabilities.

A future-ready approach

As HMRC pushes for more digital engagement and real-time compliance, the case for automation is clear. The case for group relief optimisation is less widely known, but it holds the potential to unlock significant tax savings.

Advanced group relief optimisation tools, like GroupTax.ai are designed to help in exactly this scenario. By modelling all valid surrender sequences across a group structure, they give tax teams the insights and confidence needed to make the most of what the group relief rules offer.

As tax teams strive to deliver more strategic value to their organisations, embracing systematic optimisation offers a smarter, faster way to uncover savings that might otherwise remain hidden. For tax directors managing complex groups, the question isn't whether optimisation is worthwhile—it's whether they can afford to leave these savings undiscovered.