Hamid Mojarad & Anor v The Commissioners for HMRC

Decision date: 29 May 2025

Neutral citation: [2025] UKFTT 598 (TC)

Overall AI summary confidence: high

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Short overview

This short overview is intended to summarise the case, issues and outcome so far as they are supported by the judgment.

AI confidence in this short overview: high

This appeal concerned two directors against Personal Liability Notices (PLNs) issued after HMRC varied a company VAT assessment based on an average ticket price derived from contemporaneous ticket records ("Yellow Book"). The Tribunal accepted HMRC's average (£19.65), rejected the appellants' lower estimates as unsupported, found the inaccuracies deliberate (so the paragraph 18(3) defence failed), and upheld disclosure reductions and the PLNs of £12,145.50 each. The late appeals were permitted but dismissed on the merits.

Ratio decidendi

This summary is intended to identify the ratio decidendi, meaning the legal reasons for deciding and the binding part of the decision.

AI confidence in this ratio decidendi summary: high

The Tribunal preferred an average drawn from contemporaneous business records based on a large sample over later, unsupported recollections or small samples; persistent, significant under-declarations over time can support a finding of deliberate inaccuracy; prompted disclosures do not count as unprompted for mitigation and the quality of telling/helping/giving is a matter for judgment.

Obiter dicta

This summary is intended to identify obiter dicta, meaning observations made by the way that were not necessary to deciding the case and are not binding.

AI confidence in this obiter dicta summary: medium

The judgment noted that failure to provide contemporaneous records or to substantiate alternative figures undermines challenges to HMRC calculations; merely relying on an agent without documentary evidence of instructions or records is unlikely to establish reasonable care under paragraph 18(3); and returning disputed source material to a taxpayer to enable them to ascribe missing values may affect the credibility of subsequent submissions.