Insights from the United Kingdom’s People with Significant Control register

1. Introduction

Ensuring the accuracy and reliability of beneficial ownership (BO) information is essential for it to serve its intended purposes, whether in tackling corruption, preventing money laundering, or supporting fair taxation. International standards and national regulations provide a range of verification mechanisms, including basic data validation (e.g. completeness of required fields), sworn declarations by company representatives, checks by authorised professionals, and discrepancy reporting by financial institutions.

While these measures are effective in identifying inconsistencies within individual company records, such as missing information or contradictions between registry and financial institution data, they are primarily limited to detecting internal or self-contained errors. [1] More complex forms of misreporting, such as coordinated falsehoods that are consistently reported across multiple entities, can evade detection through these standard checks.

Identifying such systemic anomalies requires a broader analytical approach. This involves first establishing what constitutes a “normal” ownership structure, then defining both expected values and variations so that deviations can be flagged as potential outliers or red flags.

With this in mind, Maria Jofre, Data Analyst at Open Ownership, and Andres Knobel, Beneficial Ownership Lead Researcher at the Tax Justice Network, collaborated to explore and analyse the ownership structures of United Kingdom (UK) legal entities. This report presents the findings of that effort. It outlines methodological challenges and best practices, and includes a reproducible Python notebook to support future analysis using BO data.

Next page: 2. Research objectives