Notes on open data and transparency

Beneficial ownership, corporate disclosure, tax justice, supply chains, policy and history

TJN Measuring Illicit Financial Flows: Introduction


This post is notes for an Open Data Services Co-operative reading group on the introductory chapter to the Tax Justice Network’s Measuring Illicit Financial Flows book. See this post for more info on the reading group.

Political goals for measuring illicit financial flows

Aim of UN SDG 16.4 is to:

by 2030 significantly reduce illicit financial and arms flows, strengthen the recovery and return of stolen assets and combat all forms of organized crime. Note that this is also a strong claim for creating, and opening up, beneficial ownerships data sets. Establishing claims on ownership over assets is a prerequisite for taxing/reclaiming/establishing harm done by assets.

The mechanism by which Illicit financial flows (IFF) affect development are outlined in two cycles by Cobham:

  • Illegal capital IFF: viscious cycle related to negative insecurity and state illegitimacy (i.e., the ability of the state to reduce the risk of conflict and violence).

IFF illegal capital cycle

Source: Cobham (2014)

  • Legal capital IFF: viscious cycle related to positive security (i.e., the ability of the state to promote conditions for economic and social development.).

IFF legal capital cycle Source: Cobham (2014)

The book

IFF methodologies prioritised that:

  • make global estimates based on country-level findings;
  • are relevant to policy;
  • illegal markets largely excluded because national estimates have not been replicated in other countries (broadly);
  • tax gaps also not considered;

Main areas:

  1. Trade-based IFF (national-level data; commodity-level data; transaction-level data);
  2. Capital accounts anomalies (Global Financial Integrity, Ndikumana and Boyce; James Henry);
  3. Combination of trade-based and capital account components;
  4. Undeclared wealth held offshore (James Henry; Gabriel Zucman);
  5. MNE profit-shifting (multilateral organisations; Kim Clausing);
  6. Alternative approaches: risk-based proxies; policy-based indicators of progress.


Tax is the first ‘means of implementation’ in the SDGs (not mentioned in the Millenium Development Goals). Can add here that the taxation of assets is rising up the agenda, including in World Bank-type circles. ‘Go after the big targets’ etc. The policy momentum is continuing with OECD’s platform for collaboration on tax.

IFF emerged as a counterpoint to the idea of corruption as a problem of the global South. Raymond Baker’s Capitalism’s Achilles Heel: scale of tax evasion dwarfed that of public corruption. The founder of Global Financial Integrity.

Profit-shifting as a motivation for country-by-country reporting. But see this thread on value creation as fiction

Secrecy jurisdictions act as a driver of IFF: opaque accounting, anonymous owners and failure to exchange information. In this context, bureaucratic frictions and limited capacity within financial intelligence units strengthen the argument for openness. See Christian Aid. “Questionable Values? A Review of Capital Economics’ Report on the British Virgin Islands,” February 2018.

IFF Indicator

But no indicator to track progress and efforts made to remove MNEs from scope(!).

UNCTAD and UNODC working towards agreement on a target. Currently this is:

16.4.1 Total value of inward and outward illicit financial flows (in current USD)

No agreement on how to measure that yet.


Legalistic definitions of IFF unsuitable (too political, too dependent on capacity).

Perhaps better to think of harm done (or risk of harm done).

Cobham (2004) identifies four components of IFF:

IFF typology

  1. Market/regulatory abuse
  2. Tax abuse.
  3. Abuse of power.
  4. Proceeds of crime.

The major actors are:

  1. Private actors (including their professional adivsors). These are the leading groups in components 1,2 and 3.
  2. Public office holders. These are important groups in components 3 and 4. They have some involvement in component 1.
  3. Criminal groups are the leading group in component 4.

Most research has focused on abuse of power and proceeds of crime; relatively little attention has been paid to market abuse and tax abuse. As a result the private sector has been neglected despite its dominant role in IFF.


Sol Picciotto argues for three categories of MNE tax avoidance, with grey areas between:

  1. Illegal evasion.
  2. Unlawful avoidance.
  3. Lawful avoidance.

Broader term of misalignment motivates BEPS to align taxable profits with MNEs actual economic activity.

IFF typology

Other posts in the Taxation reading group series: