This paper examines how structured beneficial ownership (BO) data can be used to uncover hidden ownership patterns and inform anti-money laundering (AML) efforts. Using the United Kingdom’s (UK) People with Significant Control (PSC) register, the study applies a two-stage analytical approach: first, to detect anomalous reporting patterns; and second, to analyse trust-related declarations. While trusts are widely acknowledged as high-risk vehicles for money laundering, systematic research on how they are reflected in BO data for legal entities remains limited. The study finds that entities without declared beneficial owners, with mathematically inconsistent interest configurations, and with indirect control through trusts can all be detected using publicly available data. Trust-related interests, though representing only a small share of disclosures and capturing only those arrangements explicitly declared in the PSC register, appear in some of the largest and most opaque ownership networks. However, the lack of integration between the UK’s BO, shareholder, and trust registers restricts the ability to identify all parties involved and map complete ownership chains. Closing these gaps – through improved interoperability, automated validation mechanisms, and data sharing – would significantly strengthen oversight capabilities and enhance the effectiveness of AML risk assessments. • Uses UK beneficial ownership (BO) data to detect anomalous ownership patterns • Identifies structural outliers in BO disclosures • Reveals opacity in trust-based control structures • Flags high-risk and inconsistent BO reporting • Shows how fragmented registers hinder ownership tracing
Jofre et al. (Fri,) studied this question.