Measuring the economic impact of beneficial ownership transparency (full report)

  • Publication date: 12 May 2022
  • Authors: Oxford Insights, Lateral Economics, Open Ownership


Beneficial ownership transparency (BOT) involves governments collecting beneficial ownership information [2] and making this information available to actors within and outside of government, such as law enforcement or the general public. Beneficial ownership data can then be used to tackle issues around corporate accountability and illicit financial flows, and to facilitate sanctions against corrupt officials, or actors accused of complicity in human rights abuses. [3]

The nature of BOT regimes varies significantly across jurisdictions. With effective implementation, however, BOT policies should align with Open Ownership’s principles of effective disclosure. [4] Broadly summarised, these principles state that data should be comprehensively collected and disclosed, freely available in a central register, and periodically verified, with sanctions enforced for non-compliance with disclosure obligations. Open and free-to-access BOT registries such as the UK’s PSC (Person of Significant Control) register are examples of emerging best practice in this area, even though no registry to date fully meets all of the requirements set out in the Open Ownership Principles.

Since the introduction of the first standards on beneficial ownership transparency (BOT) published by the Financial Action Task Force (FATF) in 2003, more than 113 countries have made commitments to collect more information about the individuals who own or control registered legal entities. [5] A few dozen have also created centralised beneficial ownership registers to house this information, particularly after the European Union’s 5th Anti Money Laundering Directive mandated EU states to do so in 2015. [6] [7]

Despite this surge in measures intended to increase beneficial ownership transparency, there remains only a limited body of research which seeks to assess the impact of BOT interventions, and even less work that quantitatively measures the economic impacts of BOT. Instead, most material surrounding BOT focuses on its benefits to public integrity, positing BOT as an important tool designed to tackle money laundering and other criminal activity, as opposed to a driver of economic impacts. These ‘public good’ arguments have taken on particular significance prior to the publication of this report, with BOT being highlighted as a crucial reform when looking to enforce sanctions and prevent unwanted foreign influence in the context of Russia’s invasion of Ukraine. [8] [9]

Nonetheless, the perceived lack of quantitative economic evidence for BOT limits discussions about the broader impacts and benefits of reform. According to interviewees consulted during this research, this even has the potential to act as an obstacle to further implementation, particularly for budgetary officials or business leaders seeking proof that the economic benefits of BOT outweigh the costs of reform. [10] As such, Open Ownership has identified a need to explore potential methods for measuring the economic impact of BOT, which forms the backdrop of this landscaping study.

At the outset of the project, we established a number of key research questions, including:

  • What has been done so far to measure the benefits of BOT?
  • What benefits can we expect from beneficial ownership transparency policies?
  • How (and with what level of confidence) can we attribute a benefit to beneficial ownership transparency?
  • How can we measure the scale of benefits?
  • What are the limitations and advantages of different approaches to measuring the economic impact of BOT?
  • To what extent is it possible to draw upon methodological approaches to measurement from other fields?
  • How might quantitative evidence be used to advance BOT policymaking in the future?

Measuring the economic impact of BOT is not a straightforward task. Neighbouring research teaches us that quantifying the impact of anti-corruption initiatives more generally can present challenges given the clandestine nature of criminal financial activities and the difficulties of attributing benefits to specific interventions. Similar obstacles arise when looking to measure the impact of BOT, alongside other challenges, such as concerns around data availability. This research looks to account for the ambitious nature of measuring the economic impacts of BOT by acknowledging the feasibility of potential approaches, as well as being candid about their trade offs.

Methodological note

The methodological approach to this piece of work can be broadly divided into three phases:

1) Definitions and logic modelling

During the initial phase of the project, we worked to establish clear definitions of beneficial ownership, its specific policy objectives and implementation types, which could be used as a solid foundation for approaches to measurement.

We also conducted a logic modelling exercise to map out the kinds of benefits that one could logically expect to derive from BOT, which was supported by insights from desk research and expert interviews outlined below.

2) Literature review

To understand the landscape of work on BOT benefits, we conducted a review of work which has already sought to measure the economic impact of BOT (of which we found very limited examples) and material which is more sceptical about the potential for robust econometric analysis.

Given the limited amount of literature available which specifically focussed on the economic impact of BOT, we also looked to other policy areas including fiscal transparency and open contracting and sought out learnings from economic analyses in those fields which were relevant to this piece of work.

The literature review section of this paper, found in the annex, discusses our findings in more detail.

3) Scoping interviews with experts in the beneficial ownership field

We also conducted semi-structured interviews with experts from beneficial ownership advocacy organisations, academia, and government. Some interviews were specifically tailored to participants previous work, in order to deepen our understanding of the research landscape, but broadly we asked all interviewees:

  • What benefits would they expect to arise from BOT?
  • Did they have any experience of econometric analyses of BOT?
  • What are the obstacles to measurement which might be expected?
  • Whether they had any sense of the kinds of approaches that might be pursued in the future?
  • Whether they thought measuring benefits was a priority (and if so, for whom)?

Following initial scoping interviews, we also returned to some of the experts engaged during phase 3 to discuss the approaches and recommendations identified and to solicit feedback, which has since been incorporated into this report.

Limitations, bias risks, and mitigation

Perhaps the most significant limitation of this study was the small sample size of experts consulted. Despite a short timeframe and limited expert availability, we were able to consult with 10 experts, some of whom were available for follow up interviews. Interviews provided valuable insights, which helped to shape the content of this report. However, we did have some difficulty getting access to government stakeholders. Therefore the report can offer only limited insights into particular government department approaches to impact measurement of BOT.

A further limitation is that much of the evidence included in the report is UK-centric. This is largely because the UK government has periodically published its impact assessments, post implementation reviews and service evaluations, which have been fundamental resources that have informed the discussions in the report. During the scope of this project, we were unable to find similar assessments from other jurisdictions, which could be due to a lack of public availability or that they have not yet been conducted. In order to mitigate somewhat against this bias, we reviewed literature which discusses BOT interventions in a number of countries and spoke to interviewees with expertise in a range of country contexts.

A final factor, which is perhaps not a limitation but rather indicative of the nature of this report as an explorative landscaping study, concerns the lack of literature which explicitly discusses the economic impacts of BOT. Interviews with subject matter experts helped to supplement our understanding of the benefit space of BOT where literature was not available. Broadening the literature review to include research on other forms of financial transparency, such as fiscal transparency, where a number of quantitative impact studies have already been conducted, also helped to strengthen the report’s evidence base.


[2] Open Ownership defines a beneficial owner as “a natural person who has the right to some share or enjoyment of a legal entity’s income or assets (ownership) or the right to direct or influence the entity’s activities (control)”. See Open Ownership. (2020). Beneficial ownership in law: Definitions and thresholds.

[3] Open Ownership. What is beneficial ownership transparency? Accessed March 2022.,controlled%20by%20their%20beneficial%20owners.

[4] Open Ownership. (2021). The Open Ownership Principles.

[5] Open Ownership. Worldwide commitments and action map. Accessed January 2022.

[6] Ibid.

[7] Official Journal of the European Union. (2015). Directive (EU) 2015/849 of the European Parliament and of the Council.

[8] Elgot, J. (2022). UK to expand Russia sanctions list as bill is fast-tracked. The Guardian.

[9] Open Ownership.(2021). Using beneficial ownership data for national security.

[10] Interview with subject matter experts, March 2022; Interview with advocacy organisation, January 2022.

[11] Department for International Development. (2015). Evidence Paper: Why Corruption Matters: understanding causes, effects and how to address them.

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